diff --git a/MEDiml/__init__.py b/MEDiml/__init__.py index de92c45..06e15db 100644 --- a/MEDiml/__init__.py +++ b/MEDiml/__init__.py @@ -14,7 +14,7 @@ logging.getLogger(__name__).addHandler(stream_handler) __author__ = "MEDomicsLab consortium" -__version__ = "0.9.9" +__version__ = "0.9.10" __copyright__ = "Copyright (C) MEDomicsLab consortium" __license__ = "GNU General Public License 3.0" __maintainer__ = "MAHDI AIT LHAJ LOUTFI" diff --git a/MEDiml/wrangling/DataManager.py b/MEDiml/wrangling/DataManager.py index b6fcfb3..a8f0035 100644 --- a/MEDiml/wrangling/DataManager.py +++ b/MEDiml/wrangling/DataManager.py @@ -432,17 +432,7 @@ def __associate_roi_to_image( Returns: MEDscan: Returns a MEDscan instance with updated roi attributes. """ - image_file = Path(image_file) - roi_index = 0 - - if not path_roi_data: - if not self.paths._path_to_niftis: - raise ValueError("The path to the niftis is not defined") - else: - path_roi_data = self.paths._path_to_niftis - - for file in path_roi_data.glob('*.nii.gz'): - _id = image_file.name.split("(")[0] # id is PatientID__ImagingScanName + def load_mask(_id, file, medscan): # Load the patient's ROI nifti files: if file.name.startswith(_id) and 'ROI' in file.name.split("."): roi = nib.load(file) @@ -452,8 +442,27 @@ def __associate_roi_to_image( name_set = file.name[file.name.find("_") + 2 : file.name.find("(")] medscan.data.ROI.update_indexes(key=roi_index, indexes=np.nonzero(roi_data.flatten())) medscan.data.ROI.update_name_set(key=roi_index, name_set=name_set) - medscan.data.ROI.update_roi_name(key=roi_index, roi_name=roi_name) + medscan.data.ROI.update_roi_name(key=roi_index, roi_name=roi_name) + else: + raise ValueError(f"The ROI file for patient ID: {_id} " + f"was not found in the given path: {file} or was not correctly named.") + + image_file = Path(image_file) + roi_index = 0 + if not path_roi_data: + if not self.paths._path_to_niftis: + raise ValueError("The path to the niftis is not defined") + else: + path_roi_data = self.paths._path_to_niftis + + for file in self.__nifti.stack_path_roi: + _id = image_file.name.split("(")[0] if ("(") in image_file.name else image_file.name # id is PatientID__ImagingScanName + load_mask(_id, file, medscan) roi_index += 1 + else: + _id = image_file.name.split("(")[0] if ("(") in image_file.name else image_file.name # id is PatientID__ImagingScanName + load_mask(_id, path_roi_data, medscan) + return medscan def __associate_spatialRef(self, nifti_file: Union[Path, str], medscan: MEDscan) -> MEDscan: @@ -567,7 +576,7 @@ def process_all_niftis(self) -> List[MEDscan]: medscan = MEDscan() medscan.patientID = os.path.basename(file).split("_")[0] medscan.type = os.path.basename(file).split(".")[-3] - medscan.series_description = file.name[file.name.find('__') + 2: file.name.find('(')] + medscan.series_description = file.name[file.name.find('__') + 2: file.name.find('(')] if '__' in file.name else "" medscan.format = "nifti" medscan.data.set_orientation(orientation="Axial") medscan.data.set_patient_position(patient_position="HFS") @@ -625,6 +634,24 @@ def process_all_niftis(self) -> List[MEDscan]: if list_instances: return list_instances + def process_one_nifti(self, path_image: Union[Path, str], path_mask: Union[Path, str]) -> MEDscan: + """Processes one NIfTI file to create a MEDscan class instance. + + Args: + nifti_file (Union[Path, str]): Path to the NIfTI file. + path_data (Union[Path, str]): Path to the data. + + Returns: + MEDscan: MEDscan class instance. + """ + medscan = self.__process_one_nifti(path_image, path_mask) + + # SAVE MEDscan INSTANCE + if self.save and self.paths._path_save: + save_MEDscan(medscan, self.paths._path_save) + + return medscan + def update_from_csv(self, path_csv: Union[str, Path] = None) -> None: """Updates the class from a given CSV and summarizes the processed scans again according to it. diff --git a/README.md b/README.md index 0c1884c..5ee6e70 100644 --- a/README.md +++ b/README.md @@ -3,11 +3,11 @@ [![PyPI - Python Version](https://img.shields.io/badge/python-3.8%20|%203.9%20|%203.10-blue)](https://www.python.org/downloads/release/python-380/) -[![PyPI - version](https://img.shields.io/badge/pypi-v0.9.8-blue)](https://pypi.org/project/medimage-pkg/) +[![PyPI - version](https://img.shields.io/badge/pypi-v0.9.10-blue)](https://pypi.org/project/medimage-pkg/) [![Continuous Integration](https://github.com/MEDomicsLab/MEDiml/actions/workflows/python-app.yml/badge.svg)](https://github.com/MEDomicsLab/MEDiml/actions/workflows/python-app.yml) [![Documentation Status](https://readthedocs.org/projects/mediml/badge/?version=latest)](https://mediml.readthedocs.io/en/latest/?badge=latest) [![License: GPL-3](https://img.shields.io/badge/license-GPLv3-blue)](LICENSE) -[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/MahdiAll99/MEDimage/blob/main/notebooks/tutorial/DataManager-Tutorial.ipynb) +[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/MEDomicsLab/MEDiml/blob/main/notebooks/tutorial/DataManager-Tutorial.ipynb) @@ -27,7 +27,7 @@ ## 1. Introduction MEDiml is an open-source Python package that can be used for processing multi-modal medical images (MRI, CT or PET) and for extracting their radiomic features. This package is meant to facilitate the processing of medical images and the subsequent computation of all types of radiomic features while maintaining the reproducibility of analyses. This package has been standardized with the [IBSI](https://theibsi.github.io/) norms. -![MEDiml overview](https://raw.githubusercontent.com/MahdiAll99/MEDimage/main/docs/figures/pakcage-overview.png) +![MEDiml overview](https://raw.githubusercontent.com/MEDomicsLab/MEDiml/main/docs/figures/pakcage-overview.png) ## 2. Installation @@ -107,14 +107,14 @@ The image biomarker standardization initiative ([IBSI](https://theibsi.github.io - ### IBSI Chapter 1 [The IBSI chapter 1](https://theibsi.github.io/ibsi1/) is dedicated to the standardization of commonly used radiomic features. It was initiated in September 2016 and reached completion in March 2020. We have created two [jupyter notebooks](https://github.com/MEDomicsLab/MEDiml/tree/main/notebooks/ibsi) for each phase of the chapter and made them available for the users to run the IBSI tests for themselves. The tests can also be explored in interactive Colab notebooks that are directly accessible here: - - **Phase 1**: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/MahdiAll99/MEDimage/blob/main/notebooks/ibsi/ibsi1p1.ipynb) - - **Phase 2**: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/MahdiAll99/MEDimage/blob/main/notebooks/ibsi/ibsi1p2.ipynb) + - **Phase 1**: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/MEDomicsLab/MEDiml/blob/main/notebooks/ibsi/ibsi1p1.ipynb) + - **Phase 2**: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/MEDomicsLab/MEDiml/blob/main/notebooks/ibsi/ibsi1p2.ipynb) - ### IBSI Chapter 2 [The IBSI chapter 2](https://theibsi.github.io/ibsi2/) was launched in June 2020 and reached completion in February 2024. It is dedicated to the standardization of commonly used imaging filters in radiomic studies. We have created two [jupyter notebooks](https://github.com/MEDomicsLab/MEDiml/tree/main/notebooks/ibsi) for each phase of the chapter and made them available for the users to run the IBSI tests for themselves and validate image filtering and image biomarker calculations from filter response maps. The tests can also be explored in interactive Colab notebooks that are directly accessible here: - - **Phase 1**: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/MahdiAll99/MEDimage/blob/main/notebooks/ibsi/ibsi2p1.ipynb) - - **Phase 2**: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/MahdiAll99/MEDimage/blob/main/notebooks/ibsi/ibsi2p2.ipynb) + - **Phase 1**: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/MEDomicsLab/MEDiml/blob/main/notebooks/ibsi/ibsi2p1.ipynb) + - **Phase 2**: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/MEDomicsLab/MEDiml/blob/main/notebooks/ibsi/ibsi2p2.ipynb) Our team at *UdeS* (a.k.a. Université de Sherbrooke) has already submitted the benchmarked values to the [IBSI uploading website](https://ibsi.radiomics.hevs.ch/). diff --git a/notebooks/demo/Glioma-Demo.ipynb b/notebooks/demo/Glioma-Demo.ipynb index 59f1a9a..cdde1e2 100644 --- a/notebooks/demo/Glioma-Demo.ipynb +++ b/notebooks/demo/Glioma-Demo.ipynb @@ -32,9 +32,9 @@ "\n", "We assume that you now understand the usage of most parts of the package. If that's not the case, we invite you to take a look at the available tutorials [here](https://mediml.readthedocs.io/en/latest/tutorials.html).\n", "\n", - "This is a final notebook that demonstrates the usage of the ``MEDimage`` package for one scan. It is a final demo that shows in a brief way the flexibility and the versatility of the code in radiomics analysis. We will use a **[glioma TCGA](https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga)** cancer scan.\n", + "This is a final notebook that demonstrates the usage of the ``MEDiml`` package for one scan. It is a final demo that shows in a brief way the flexibility and the versatility of the code in radiomics analysis. We will use a **[glioma TCGA](https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga)** cancer scan.\n", "\n", - "**Extra**: This notebook also demonstrates an extra feature of ``MEDimage`` which is mask cropping (ROI boxing) that could be useful for running radiomics analysis with a scan box around the ROI only instead of the full scan.\n" + "**Extra**: This notebook also demonstrates an extra feature of ``MEDiml`` which is mask cropping (ROI boxing) that could be useful for running radiomics analysis with a scan box around the ROI only instead of the full scan.\n" ] }, { @@ -58,45 +58,16 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 21, "id": "af05f061", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "PyCUDA is not installed. Please install it to use the textural filters.\n" - ] - }, - { - "ename": "ImportError", - "evalue": "cannot import name '_format_load_msg' from 'joblib.memory' (/home/local/USHERBROOKE/aitm2302/anaconda3/envs/testpypi/lib/python3.9/site-packages/joblib/memory.py)", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mImportError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[1], line 5\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01msys\u001b[39;00m\n\u001b[1;32m 3\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mpathlib\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Path\n\u001b[0;32m----> 5\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mMEDimage\u001b[39;00m\n\u001b[1;32m 6\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mnumpy\u001b[39;00m 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\u001b[0;32m~/anaconda3/envs/testpypi/lib/python3.9/site-packages/pycaret/internal/memory.py:25\u001b[0m\n\u001b[1;32m 22\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtyping\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m TYPE_CHECKING, Union\n\u001b[1;32m 24\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mjoblib\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mhashing\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Hasher, Pickler\n\u001b[0;32m---> 25\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mjoblib\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mmemory\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[1;32m 26\u001b[0m MemorizedFunc,\n\u001b[1;32m 27\u001b[0m MemorizedResult,\n\u001b[1;32m 28\u001b[0m Memory,\n\u001b[1;32m 29\u001b[0m NotMemorizedResult,\n\u001b[1;32m 30\u001b[0m _format_load_msg,\n\u001b[1;32m 31\u001b[0m filter_args,\n\u001b[1;32m 32\u001b[0m format_call,\n\u001b[1;32m 33\u001b[0m format_signature,\n\u001b[1;32m 34\u001b[0m format_time,\n\u001b[1;32m 35\u001b[0m get_func_name,\n\u001b[1;32m 36\u001b[0m )\n\u001b[1;32m 37\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mxxhash\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m xxh128 \u001b[38;5;28;01mas\u001b[39;00m xxh\n\u001b[1;32m 39\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n", - "\u001b[0;31mImportError\u001b[0m: cannot import name '_format_load_msg' from 'joblib.memory' (/home/local/USHERBROOKE/aitm2302/anaconda3/envs/testpypi/lib/python3.9/site-packages/joblib/memory.py)" - ] - } - ], + "outputs": [], "source": [ "import os\n", "import sys\n", "from pathlib import Path\n", "\n", - "import MEDimage\n", + "import MEDiml\n", "import numpy as np" ] }, @@ -112,7 +83,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "id": "bcb661b0", "metadata": {}, "outputs": [], @@ -121,7 +92,7 @@ "\n", "path_data = Path(os.getcwd()) / 'data' / 'Glioma-TCGA-02-0003__T1.MRscan.npy'\n", "with open(path_data, 'rb') as f: medscan = pickle.load(f)\n", - "medscan = MEDimage.MEDscan(medscan)" + "medscan = MEDiml.MEDscan(medscan)" ] }, { @@ -150,12 +121,12 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "id": "b905c572", "metadata": {}, "outputs": [], "source": [ - "vol_obj_init, roi_obj_init = MEDimage.processing.get_roi_from_indexes(\n", + "vol_obj_init, roi_obj_init = MEDiml.processing.get_roi_from_indexes(\n", " medscan,\n", " name_roi='{ED}+{ET}+{NET}',\n", " box_string='full')" @@ -172,15 +143,16 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 24, "id": "40fcdead", "metadata": {}, "outputs": [], "source": [ - "local_intensity = MEDimage.biomarkers.local_intensity.extract_all(\n", + "local_intensity = MEDiml.biomarkers.local_intensity.extract_all(\n", " img_obj=vol_obj_init.data,\n", " roi_obj=roi_obj_init.data,\n", - " res=[2, 2, 3]\n", + " res=[2, 2, 3],\n", + " intensity_type='arbitrary',\n", " )" ] }, @@ -194,12 +166,12 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 25, "id": "975a791c", "metadata": {}, "outputs": [], "source": [ - "local_intensity_peak = MEDimage.biomarkers.local_intensity.peak_local(\n", + "local_intensity_peak = MEDiml.biomarkers.local_intensity.peak_local(\n", " img_obj=vol_obj_init.data,\n", " roi_obj=roi_obj_init.data,\n", " res=[2, 2, 3]\n", @@ -216,14 +188,14 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 26, "id": "3982b4ab", "metadata": {}, "outputs": [], "source": [ "# Interpolation\n", "# Intensity Mask\n", - "vol_obj = MEDimage.processing.interp_volume(\n", + "vol_obj = MEDiml.processing.interp_volume(\n", " vol_obj_s=vol_obj_init,\n", " roi_obj_s=roi_obj_init,\n", " vox_dim=[2, 2, 3],\n", @@ -233,7 +205,7 @@ " box_string=\"full\"\n", ")\n", "# Morphological Mask\n", - "roi_obj_morph = MEDimage.processing.interp_volume(\n", + "roi_obj_morph = MEDiml.processing.interp_volume(\n", " vol_obj_s=roi_obj_init,\n", " roi_obj_s=roi_obj_init,\n", " vox_dim=[2, 2, 3],\n", @@ -256,7 +228,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 27, "id": "9ed982ae", "metadata": {}, "outputs": [], @@ -266,14 +238,14 @@ "# Re-segmentation\n", "# Intensity mask range re-segmentation\n", "roi_obj_int = deepcopy(roi_obj_morph)\n", - "roi_obj_int.data = MEDimage.processing.range_re_seg(\n", + "roi_obj_int.data = MEDiml.processing.range_re_seg(\n", " vol=vol_obj.data, \n", " roi=roi_obj_int.data,\n", " im_range=[-500, 400]\n", ")\n", "# Intensity mask outlier re-segmentation\n", "roi_obj_int.data = np.logical_and(\n", - " MEDimage.processing.outlier_re_seg(\n", + " MEDiml.processing.outlier_re_seg(\n", " vol=vol_obj.data, \n", " roi=roi_obj_int.data, \n", " outliers=''\n", @@ -292,12 +264,12 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 28, "id": "97dd287c", "metadata": {}, "outputs": [], "source": [ - "vol_int_re = MEDimage.processing.roi_extract(\n", + "vol_int_re = MEDiml.processing.roi_extract(\n", " vol=vol_obj.data, \n", " roi=roi_obj_int.data\n", ")" @@ -313,12 +285,12 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 30, "id": "1983e641", "metadata": {}, "outputs": [], "source": [ - "stats = MEDimage.biomarkers.stats.extract_all(vol=vol_int_re)" + "stats = MEDiml.biomarkers.stats.extract_all(vol=vol_int_re, intensity_type='arbitrary')" ] }, { @@ -332,12 +304,47 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 31, "id": "c0b50912", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "{'Fcm_joint_max': 0.0016778523489932886,\n", + " 'Fcm_joint_avg': 372.03796140939596,\n", + " 'Fcm_joint_var': 923.214792152873,\n", + " 'Fcm_joint_entr': 10.21245711106619,\n", + " 'Fcm_diff_avg': 21.386325503355707,\n", + " 'Fcm_diff_var': 786.4581351557925,\n", + " 'Fcm_diff_entr': 7.965902141630304,\n", + " 'Fcm_sum_avg': 744.0759228187919,\n", + " 'Fcm_sum_var': 2449.0261149202174,\n", + " 'Fcm_sum_entr': 8.683223590927662,\n", + " 'Fcm_energy': 0.0008445565515066891,\n", + " 'Fcm_contrast': 1243.8330536912752,\n", + " 'Fcm_dissimilarity': 21.386325503355703,\n", + " 'Fcm_inv_diff': 0.1340401104247356,\n", + " 'Fcm_inv_diff_norm': 0.9166501446905972,\n", + " 'Fcm_inv_diff_mom': 0.0687299658265903,\n", + " 'Fcm_inv_diff_mom_norm': 0.9771808043523809,\n", + " 'Fcm_inv_var': 0.35790780102435327,\n", + " 'Fcm_corr': 0.32635770989395946,\n", + " 'Fcm_auto_corr': 138713.54299496644,\n", + " 'Fcm_clust_tend': 2449.0261149202174,\n", + " 'Fcm_clust_shade': -201810.43509673234,\n", + " 'Fcm_clust_prom': 41649414.51934898,\n", + " 'Fcm_info_corr1': -0.5891829704064105,\n", + " 'Fcm_info_corr2': 0.9999012496088444}" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "glcm = MEDimage.biomarkers.glcm.extract_all(\n", + "glcm = MEDiml.biomarkers.glcm.extract_all(\n", " vol=vol_int_re, \n", " dist_correction=False\n", " )\n", @@ -355,17 +362,28 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 32, "id": "20ffaf9c", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "(0.0016778523489932886, 372.03796140939596)" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# Computation of GLCM matrix\n", - "glc_matrix = MEDimage.biomarkers.glcm.get_glcm_matrices(vol_int_re)\n", + "glc_matrix = MEDiml.biomarkers.glcm.get_glcm_matrices(vol_int_re)\n", "# Extraction of joint maximum feature\n", - "joint_max = MEDimage.biomarkers.glcm.joint_max(glc_matrix)\n", + "joint_max = MEDiml.biomarkers.glcm.joint_max(glc_matrix)\n", "# Extraction of joint average feature\n", - "joint_avg = MEDimage.biomarkers.glcm.joint_avg(glc_matrix)\n", + "joint_avg = MEDiml.biomarkers.glcm.joint_avg(glc_matrix)\n", "joint_max, joint_avg" ] }, @@ -395,12 +413,12 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 33, "id": "0f77fc8a", "metadata": {}, "outputs": [], "source": [ - "vol_obj = MEDimage.filters.apply_laws(\n", + "vol_obj = MEDiml.filters.apply_laws(\n", " input_images=vol_obj,\n", " config=[\"E3\", \"W5\", \"R5\"],\n", " padding=\"symmetric\",\n", @@ -418,12 +436,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 34, "id": "0e1d6630", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "12.420325523121914" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "peak_local_intensity = MEDimage.biomarkers.local_intensity.peak_local(\n", + "peak_local_intensity = MEDiml.biomarkers.local_intensity.peak_local(\n", " img_obj=vol_obj.data,\n", " roi_obj=vol_obj.data,\n", " res=[2, 2, 3]\n", @@ -457,10 +486,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 35, "id": "23ab55ef", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "import matplotlib.pyplot as plt\n", "\n", @@ -487,7 +527,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 47, "id": "95a6de39", "metadata": { "scrolled": true @@ -495,8 +535,8 @@ "outputs": [], "source": [ "# crop the initial imaging data\n", - "crop_shape = [56, 122, 82] # All elements of crop_shape must be an even number (in voxels not in mm)\n", - "new_image, new_roi = MEDimage.processing.crop_box(vol_obj_init.data, roi_obj_init.data, crop_shape)" + "crop_shape = [128, 112, 82] # All elements of crop_shape must be an even number (in voxels not in mm)\n", + "new_image, new_roi = MEDiml.processing.crop_box(vol_obj_init.data, roi_obj_init.data, crop_shape)" ] }, { @@ -509,10 +549,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 48, "id": "2fadee07", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "_slice = 30 # index of slice that will be plotted\n", "plt.figure(figsize=(8,8))\n", @@ -552,12 +603,12 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 49, "id": "7ac74fc3", "metadata": {}, "outputs": [], "source": [ - "local_intensity_peak_cropped = MEDimage.biomarkers.local_intensity.peak_local(\n", + "local_intensity_peak_cropped = MEDiml.biomarkers.local_intensity.peak_local(\n", " img_obj=vol_obj_init.data,\n", " roi_obj=roi_obj_init.data,\n", " res=[2, 2, 3]\n", @@ -574,10 +625,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 50, "id": "6751250e", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "(834.9589, 834.9589)" + ] + }, + "execution_count": 50, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "local_intensity_peak, local_intensity_peak_cropped" ] @@ -589,7 +651,7 @@ "source": [ "## Conclusion\n", "\n", - "This final demo shows how flexible the ``MEDimage`` package can be which makes it a useful tool for reproducible image processing and features extraction." + "This final demo shows how flexible the ``MEDiml`` package can be which makes it a useful tool for reproducible image processing and features extraction." ] } ], @@ -598,9 +660,9 @@ "hash": "690809811b19584f778c4442b934fd193633a60aa2ec602bd8e4817043639bc9" }, "kernelspec": { - "display_name": "testpypi", + "display_name": "mediml", "language": "python", - "name": "testpypi" + "name": "mediml" }, "language_info": { "codemirror_mode": { @@ -612,7 +674,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.13" + "version": "3.9.19" } }, "nbformat": 4, diff --git a/notebooks/demo/data/Glioma-TCGA-02-0003__T1.MRscan.npy b/notebooks/demo/data/Glioma-TCGA-02-0003__T1.MRscan.npy index b385531..2376f4c 100644 Binary files a/notebooks/demo/data/Glioma-TCGA-02-0003__T1.MRscan.npy and b/notebooks/demo/data/Glioma-TCGA-02-0003__T1.MRscan.npy differ diff --git a/notebooks/ibsi/ibsi1p1.ipynb b/notebooks/ibsi/ibsi1p1.ipynb index 9da765e..f3b584f 100644 --- a/notebooks/ibsi/ibsi1p1.ipynb +++ b/notebooks/ibsi/ibsi1p1.ipynb @@ -33,11 +33,11 @@ "### Introduction\n", "\n", "\n", - "We recommend to take a look at the [MEDscan-tutorial notebook](https://colab.research.google.com/github/MahdiAll99/MEDimage/blob/dev/notebooks/tutorial/MEDimage-Tutorial.ipynb) and the [DataManager-tutorial](https://colab.research.google.com/github/MahdiAll99/MEDimage/blob/dev/notebooks/tutorial/DataManager-Tutorial.ipynb) before running the IBSI tests.\n", + "We recommend to take a look at the [MEDscan-tutorial notebook](https://colab.research.google.com/github/MEDomicsLab/MEDiml/blob/dev/notebooks/tutorial/MEDscan-Tutorial.ipynb) and the [DataManager-tutorial](https://colab.research.google.com/github/MEDomicsLab/MEDiml/blob/dev/notebooks/tutorial/DataManager-Tutorial.ipynb) before running the IBSI tests.\n", "\n", "In this notebook we treat the first phase of standardization of image processing and feature computation. In the figure below, we focus on the first part referred as phase 1. We only compute radiomics features from a digital phantom without any processing\n", "\n", - "\"range\n" + "\"range" ] }, { @@ -45,8 +45,15 @@ "id": "93d06dd8", "metadata": {}, "source": [ + "#### ⚠️ DOWNLOADING THE PHANTOM IS REQUIRED ⚠️\n", + "\n", "### Dataset - Digital phantom\n", - "In this chapter and in this phase, reference values for features were obtained using a digital image phantom, which is described below. The digital phantom can be found here: https://github.com/theibsi/data_sets/tree/master/ibsi_1_digital_phantom" + "\n", + "In this chapter and in this phase, reference values for features were obtained using a digital image phantom, which is described below. The digital phantom can be found here: https://github.com/theibsi/data_sets/tree/master/ibsi_1_digital_phantom\n", + "\n", + "**Please place the phantom in the following path: \"*notebooks/ibsi/data*\"**\n", + "\n", + "We recommend using the following tool to download data from GitHub: https://download-directory.github.io/" ] }, { @@ -79,7 +86,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "PyCUDA is not installed. Please install it to use the textural filters.\n" + "PyCUDA is not installed. Please install it to use the textural filters. No module named 'pycuda'\n" ] } ], @@ -90,7 +97,7 @@ "from copy import deepcopy\n", "from pathlib import Path\n", "\n", - "import MEDimage" + "import MEDiml" ] }, { @@ -100,22 +107,10 @@ "source": [ "### Classes initialization\n", "In the IBSI scripts we are going to use the *MEDscan* class and other processing classes like *DataManager* to process the imaging data and to extract the radiomics features.\n", - "- ``MEDscan``: Is a Python class that organizes all scan data and many other useful information that is used by the many processing and computing methods. Learn more in the [MEDscan-tutorial](https://colab.research.google.com/github/MahdiAll99/MEDimage/blob/dev/notebooks/tutorial/MEDscan-Tutorial.ipynb)\n", - "- ``DataManager``: A Python class that process all the raw data (DICOM and NIfTI) and convert it to *MEDimage* class objects. Learn more in the [DataManager-tutorial](https://colab.research.google.com/github/MahdiAll99/MEDimage/blob/dev/notebooks/tutorial/DataManager-Tutorial.ipynb)\n", + "- ``MEDscan``: Is a Python class that organizes all scan data and many other useful information that is used by the many processing and computing methods. Learn more in the [MEDscan-tutorial](https://colab.research.google.com/github/MEDomicsLab/MEDiml/blob/dev/notebooks/tutorial/MEDscan-Tutorial.ipynb)\n", + "- ``DataManager``: A Python class that process all the raw data (DICOM and NIfTI) and convert it to *MEDiml* class objects. Learn more in the [DataManager-tutorial](https://colab.research.google.com/github/MEDomicsLab/MEDiml/blob/dev/notebooks/tutorial/DataManager-Tutorial.ipynb)\n", "\n", - "So the first step is to initialize the MEDimage class using the *DataManager*. This class will only need path to where the data is located (either DICOM or NIfTI). We will use NIfTI for this tutorial." - ] - }, - { - "cell_type": "markdown", - "id": "e79831d7", - "metadata": {}, - "source": [ - "Make sure your folder structure looks like this:\n", - "\n", - "\n", - "\n", - "Make sure to also download the [Phantom data](https://github.com/theibsi/data_sets/tree/master/ibsi_1_digital_phantom/dicom) (we recommend you use NIfTI files) and place it in Phantom folder. The settings file can be found in the repository and is automatically place in the settings folder." + "So the first step is to initialize the MEDiml class using the *DataManager*. This class will only need path to where the data is located (either DICOM or NIfTI). We will use NIfTI for this tutorial." ] }, { @@ -133,9 +128,11 @@ "metadata": {}, "outputs": [], "source": [ - "path_settings = Path(os.getcwd()) / \"settings\" # Path to the script settings/configuration folder\n", + "# Path to the script settings/configuration folder\n", + "path_settings = Path(os.getcwd()) / \"settings\"\n", + "\n", "# Load script parameters\n", - "im_params = MEDimage.utils.json_utils.load_json(path_settings / 'Phase1_settings.json')" + "im_params = MEDiml.utils.json_utils.load_json(path_settings / 'Phase1_settings.json')" ] }, { @@ -153,59 +150,37 @@ "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "--> Scanning all folders in initial directory\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|██████████████████████████████████████████████████████████████████████████████████████████████████████| 4/4 [00:00<00:00, 52265.47it/s]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DONE\n", - "--> Reading all NIfTI objects (imaging volumes & masks) to create MEDscan classes\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - " 0%| | 0/2 [00:00 6\u001b[0m MEDinstance \u001b[38;5;241m=\u001b[39m \u001b[43mdm\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mprocess_one_nifti\u001b[49m(\n\u001b[0;32m 7\u001b[0m path_to_niftis \u001b[38;5;241m/\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mimage\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m/\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mphantom__CT(tumor).CTscan.nii.gz\u001b[39m\u001b[38;5;124m\"\u001b[39m, \n\u001b[0;32m 8\u001b[0m path_to_niftis \u001b[38;5;241m/\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmask\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m/\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mphantom__CT(tumor).ROI.nii.gz\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 9\u001b[0m )\n", + "\u001b[1;31mAttributeError\u001b[0m: 'DataManager' object has no attribute 'process_one_nifti'" ] } ], "source": [ "# Intialize the DataManager class\n", "path_to_niftis = Path(os.getcwd()) / \"data\" / \"Phantom\"\n", - "dm = MEDimage.wrangling.DataManager(path_to_niftis=path_to_niftis)\n", + "dm = MEDiml.wrangling.DataManager(path_to_niftis=path_to_niftis)\n", "\n", "# Process the NIfTI scan\n", - "MEDinstance = dm.process_all_niftis()[0] # one-element list/ one scan" + "MEDinstance = dm.process_one_nifti(\n", + " path_to_niftis / \"image\" / \"phantom__CT(tumor).CTscan.nii.gz\", \n", + " path_to_niftis / \"mask\" / \"phantom__CT(tumor).ROI.nii.gz\"\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e8965355-63d9-40cd-bde3-06aade53c505", + "metadata": {}, + "outputs": [], + "source": [ + "MEDinstance.data.ROI.roi_names" ] }, { @@ -215,18 +190,18 @@ "source": [ "### Image processing\n", "\n", - "In the MEDimage package, the ``processing`` module offers many methods and functionalities for image processing (interpolation, segmentation...) and will be used in this phase, but we only need to to extract the ROI and replace the excluded values (values outside the ROI) in the image volume with a placeholder (NaN). The intensity and morphological mask are identical in this case (no re-segmentation or interpolation is done here)." + "In the MEDiml package, the ``processing`` module offers many methods and functionalities for image processing (interpolation, segmentation...) and will be used in this phase, but we only need to to extract the ROI and replace the excluded values (values outside the ROI) in the image volume with a placeholder (NaN). The intensity and morphological mask are identical in this case (no re-segmentation or interpolation is done here)." ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "bc0c4790", "metadata": {}, "outputs": [], "source": [ "# Extraction of ROI mask :\n", - "vol_obj_init, roi_obj_init = MEDimage.processing.get_roi_from_indexes(MEDinstance,\n", + "vol_obj_init, roi_obj_init = MEDiml.processing.get_roi_from_indexes(MEDinstance,\n", " name_roi='{tumor}',\n", " box_string='full')\n", "\n", @@ -244,7 +219,7 @@ "MEDinstance.init_ntf_calculation(vol_obj)\n", "\n", "# Image volume ROI Extraction :\n", - "vol_int_re = MEDimage.processing.roi_extract(\n", + "vol_int_re = MEDiml.processing.roi_extract(\n", " vol=vol_obj.data, \n", " roi=roi_obj_int.data\n", ")" @@ -276,14 +251,14 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "cbd48457", "metadata": { "scrolled": true }, "outputs": [], "source": [ - "morph = MEDimage.biomarkers.morph.extract_all(\n", + "morph = MEDiml.biomarkers.morph.extract_all(\n", " vol=vol_obj.data, \n", " mask_int=roi_obj_int.data, \n", " mask_morph=roi_obj_morph.data,\n", @@ -305,12 +280,12 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "8de3dfc5", "metadata": {}, "outputs": [], "source": [ - "local_intensity = MEDimage.biomarkers.local_intensity.extract_all(\n", + "local_intensity = MEDiml.biomarkers.local_intensity.extract_all(\n", " img_obj=vol_obj.data,\n", " roi_obj=roi_obj_int.data,\n", " res=MEDinstance.params.process.scale_non_text,\n", @@ -331,12 +306,12 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "f91a2145", "metadata": {}, "outputs": [], "source": [ - "stats = MEDimage.biomarkers.stats.extract_all(\n", + "stats = MEDiml.biomarkers.stats.extract_all(\n", " vol=vol_int_re,\n", " intensity_type=\"definite\"\n", " )" @@ -344,38 +319,10 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "ed068427-0823-4788-ab43-dee44f728fe8", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'Fstat_mean': 2.1486487,\n", - " 'Fstat_var': 3.0454712,\n", - " 'Fstat_skew': 1.0838206041847196,\n", - " 'Fstat_kurt': -0.3546205634536057,\n", - " 'Fstat_median': 1.0,\n", - " 'Fstat_min': 1.0,\n", - " 'Fstat_P10': 1.0,\n", - " 'Fstat_P90': 4.0,\n", - " 'Fstat_max': 6.0,\n", - " 'Fstat_iqr': 3.0,\n", - " 'Fstat_range': 5.0,\n", - " 'Fstat_mad': 1.5522282,\n", - " 'Fstat_rmad': 1.1138338,\n", - " 'Fstat_medad': 1.1486486,\n", - " 'Fstat_cov': 0.8121978,\n", - " 'Fstat_qcod': 0.6,\n", - " 'Fstat_energy': 567.0,\n", - " 'Fstat_rms': 2.7680612}" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "stats" ] @@ -393,12 +340,12 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "id": "e9e53184", "metadata": {}, "outputs": [], "source": [ - "int_hist = MEDimage.biomarkers.intensity_histogram.extract_all(vol=vol_int_re)" + "int_hist = MEDiml.biomarkers.intensity_histogram.extract_all(vol=vol_int_re)" ] }, { @@ -415,12 +362,12 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "id": "9fc60011", "metadata": {}, "outputs": [], "source": [ - "int_vol_hist = MEDimage.biomarkers.int_vol_hist.extract_all(\n", + "int_vol_hist = MEDiml.biomarkers.int_vol_hist.extract_all(\n", " medscan=MEDinstance,\n", " vol=vol_int_re,\n", " vol_int_re=vol_int_re, \n", @@ -455,7 +402,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "id": "5bc89af2", "metadata": {}, "outputs": [], @@ -467,7 +414,7 @@ "MEDinstance.init_tf_calculation(algo=0, gl=0, scale=0)\n", "\n", "# ROI Extraction :\n", - "vol_quant_re = MEDimage.processing.roi_extract(\n", + "vol_quant_re = MEDiml.processing.roi_extract(\n", " vol=vol_obj.data, \n", " roi=roi_obj_int.data)" ] @@ -486,12 +433,12 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "id": "b1ba460c", "metadata": {}, "outputs": [], "source": [ - "glcm = MEDimage.biomarkers.glcm.extract_all(\n", + "glcm = MEDiml.biomarkers.glcm.extract_all(\n", " vol=vol_quant_re, \n", " dist_correction=MEDinstance.params.radiomics.glcm.dist_correction)" ] @@ -510,12 +457,12 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, "id": "ffc856b0", "metadata": {}, "outputs": [], "source": [ - "glrlm = MEDimage.biomarkers.glrlm.extract_all(\n", + "glrlm = MEDiml.biomarkers.glrlm.extract_all(\n", " vol=vol_quant_re,\n", " dist_correction=MEDinstance.params.radiomics.glrlm.dist_correction)" ] @@ -533,14 +480,14 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "id": "f3ab15dd", "metadata": { "scrolled": true }, "outputs": [], "source": [ - "glszm = MEDimage.biomarkers.glszm.extract_all(vol=vol_quant_re)" + "glszm = MEDiml.biomarkers.glszm.extract_all(vol=vol_quant_re)" ] }, { @@ -557,12 +504,12 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "id": "96a026c2", "metadata": {}, "outputs": [], "source": [ - "gldzm = MEDimage.biomarkers.gldzm.extract_all(\n", + "gldzm = MEDiml.biomarkers.gldzm.extract_all(\n", " vol_int=vol_quant_re, \n", " mask_morph=roi_obj_morph.data)" ] @@ -580,12 +527,12 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": null, "id": "18ea2f75", "metadata": {}, "outputs": [], "source": [ - "ngtdm = MEDimage.biomarkers.ngtdm.extract_all(\n", + "ngtdm = MEDiml.biomarkers.ngtdm.extract_all(\n", " vol=vol_quant_re, \n", " dist_correction=MEDinstance.params.radiomics.ngtdm.dist_correction)" ] @@ -603,12 +550,12 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": null, "id": "c7b48e08", "metadata": {}, "outputs": [], "source": [ - "ngldm = MEDimage.biomarkers.ngldm.extract_all(vol=vol_quant_re)" + "ngldm = MEDiml.biomarkers.ngldm.extract_all(vol=vol_quant_re)" ] }, { @@ -618,12 +565,12 @@ "source": [ "#### Update the radiomics structure\n", "\n", - "This can be done by calling the *MEDimage* class method ``update_radiomics``" + "This can be done by calling the *MEDiml* class method ``update_radiomics``" ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": null, "id": "0169e310", "metadata": {}, "outputs": [], @@ -653,238 +600,10 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": null, "id": "b50a025e", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{\n", - " \"morph_3D\": {\n", - " \"scale2\": {\n", - " \"Fmorph_vol\": 556.3333333333334,\n", - " \"Fmorph_approx_vol\": 592.0,\n", - " \"Fmorph_area\": 388.0706298811092,\n", - " \"Fmorph_av\": 0.6975505629977996,\n", - " \"Fmorph_comp_1\": 0.04105763998875515,\n", - " \"Fmorph_comp_2\": 0.5989495056264417,\n", - " \"Fmorph_sph_dispr\": 1.1863238540244057,\n", - " \"Fmorph_sphericity\": 0.8429401437117419,\n", - " \"Fmorph_asphericity\": 0.1863238540244052,\n", - " \"Fmorph_com\": 0.6715449258791162,\n", - " \"Fmorph_diam\": 13.114877048604,\n", - " \"Fmorph_pca_major\": 11.402387266727741,\n", - " \"Fmorph_pca_minor\": 9.308010776621932,\n", - " \"Fmorph_pca_least\": 8.535981219598838,\n", - " \"Fmorph_pca_elongation\": 0.816321228080262,\n", - " \"Fmorph_pca_flatness\": 0.7486135157421726,\n", - " \"Fmorph_v_dens_aabb\": 0.8692708333333334,\n", - " \"Fmorph_a_dens_aabb\": 0.8662290845560473,\n", - " \"Fmorph_v_dens_ombb\": 0.8692708333333334,\n", - " \"Fmorph_a_dens_ombb\": 0.8662290845560473,\n", - " \"Fmorph_v_dens_aee\": 1.172817247682943,\n", - " \"Fmorph_a_dens_aee\": 1.3551287345086926,\n", - " \"Fmorph_v_dens_mvee\": 0.4487938537177223,\n", - " \"Fmorph_a_dens_mvee\": 0.6963256023315707,\n", - " \"Fmorph_v_dens_conv_hull\": 0.9608520437535985,\n", - " \"Fmorph_a_dens_conv_hull\": 1.032868843228057,\n", - " \"Fmorph_integ_int\": 1195.3649150530498,\n", - " \"Fmorph_moran_i\": [],\n", - " \"Fmorph_geary_c\": []\n", - " }\n", - " },\n", - " \"locInt_3D\": {\n", - " \"scale2\": {\n", - " \"Floc_peak_local\": 2.5999999046325684,\n", - " \"Floc_peak_global\": []\n", - " }\n", - " },\n", - " \"stats_3D\": {\n", - " \"scale2\": {\n", - " \"Fstat_mean\": 2.148648738861084,\n", - " \"Fstat_var\": 3.04547119140625,\n", - " \"Fstat_skew\": 1.0838206041847196,\n", - " \"Fstat_kurt\": -0.3546205634536057,\n", - " \"Fstat_median\": 1.0,\n", - " \"Fstat_min\": 1.0,\n", - " \"Fstat_P10\": 1.0,\n", - " \"Fstat_P90\": 4.0,\n", - " \"Fstat_max\": 6.0,\n", - " \"Fstat_iqr\": 3.0,\n", - " \"Fstat_range\": 5.0,\n", - " \"Fstat_mad\": 1.5522282123565674,\n", - " \"Fstat_rmad\": 1.1138337850570679,\n", - " \"Fstat_medad\": 1.1486486196517944,\n", - " \"Fstat_cov\": 0.8121978044509888,\n", - " \"Fstat_qcod\": 0.6,\n", - " \"Fstat_energy\": 567.0,\n", - " \"Fstat_rms\": 2.7680611610412598\n", - " }\n", - " },\n", - " \"intHist_3D\": {\n", - " \"scale2_algo_bin\": {\n", - " \"Fih_mean\": 2.1486486486486487,\n", - " \"Fih_var\": 3.045471146822498,\n", - " \"Fih_skew\": 1.083820722557456,\n", - " \"Fih_kurt\": -0.35462048068783414,\n", - " \"Fih_median\": 1.0,\n", - " \"Fih_min\": 1.0,\n", - " \"Fih_P10\": 1.0,\n", - " \"Fih_P90\": 4.0,\n", - " \"Fih_max\": 6.0,\n", - " \"Fih_mode\": 1,\n", - " \"Fih_iqr\": 3.0,\n", - " \"Fih_range\": 5.0,\n", - " \"Fih_mad\": 1.5522282123565674,\n", - " \"Fih_rmad\": 1.1138337850570679,\n", - " \"Fih_medad\": 1.1486486196517944,\n", - " \"Fih_cov\": 0.8121978044509888,\n", - " \"Fih_qcod\": 0.6,\n", - " \"Fih_entropy\": 1.2656115555865246,\n", - " \"Fih_uniformity\": 0.5124178232286339,\n", - " \"Fih_max_grad\": 8.0,\n", - " \"Fih_max_grad_gl\": 3.0,\n", - " \"Fih_min_grad\": -50.0,\n", - " \"Fih_min_grad_gl\": 1.0\n", - " }\n", - " },\n", - " \"intVolHist_3D\": {\n", - " \"scale2_algoNone_bin1\": {\n", - " \"Fivh_V10\": 0.32432432432432434,\n", - " \"Fivh_V90\": 0.09459459459459463,\n", - " \"Fivh_I10\": 5.0,\n", - " \"Fivh_I90\": 2.0,\n", - " \"Fivh_V10minusV90\": 0.22972972972972971,\n", - " \"Fivh_I10minusI90\": 3.0,\n", - " \"Fivh_auc\": 0.32027027027027033\n", - " }\n", - " },\n", - " \"texture\": {\n", - " \"glcm_3D_comb\": {\n", - " \"scale2_algoFBN_bin32\": {\n", - " \"Fcm_joint_max\": 0.50853889943074,\n", - " \"Fcm_joint_avg\": 2.1489563567362433,\n", - " \"Fcm_joint_var\": 3.132460960144601,\n", - " \"Fcm_joint_entr\": 2.5738963770752696,\n", - " \"Fcm_diff_avg\": 1.3795066413662238,\n", - " \"Fcm_diff_var\": 3.21460848525001,\n", - " \"Fcm_diff_entr\": 1.6408766743670586,\n", - " \"Fcm_sum_avg\": 4.297912713472486,\n", - " \"Fcm_sum_var\": 7.412196781754876,\n", - " \"Fcm_sum_entr\": 2.1098633717396242,\n", - " \"Fcm_energy\": 0.2909508909764555,\n", - " \"Fcm_contrast\": 5.11764705882353,\n", - " \"Fcm_dissimilarity\": 1.379506641366224,\n", - " \"Fcm_inv_diff\": 0.6876976597090448,\n", - " \"Fcm_inv_diff_norm\": 0.8558983710786366,\n", - " \"Fcm_inv_diff_mom\": 0.6306378630856809,\n", - " \"Fcm_inv_diff_mom_norm\": 0.902210369762552,\n", - " \"Fcm_inv_var\": 0.057444655281467416,\n", - " \"Fcm_corr\": 0.18312676136476327,\n", - " \"Fcm_auto_corr\": 5.191650853889944,\n", - " \"Fcm_clust_tend\": 7.4121967817548775,\n", - " \"Fcm_clust_shade\": 17.41920541588659,\n", - " \"Fcm_clust_prom\": 147.46389960668296,\n", - " \"Fcm_info_corr1\": -0.028799723193268463,\n", - " \"Fcm_info_corr2\": 0.2691687308895439\n", - " }\n", - " },\n", - " \"glrlm_3D_comb\": {\n", - " \"scale2_algoFBN_bin32\": {\n", - " \"Frlm_sre\": 0.7291271661569827,\n", - " \"Frlm_lre\": 2.761467889908257,\n", - " \"Frlm_lgre\": 0.606651376146789,\n", - " \"Frlm_hgre\": 9.637614678899082,\n", - " \"Frlm_srlge\": 0.3716031626363877,\n", - " \"Frlm_srhge\": 8.672350492694529,\n", - " \"Frlm_lrlge\": 2.162865273530411,\n", - " \"Frlm_lrhge\": 15.634556574923547,\n", - " \"Frlm_glnu\": 281.28134556574923,\n", - " \"Frlm_glnu_norm\": 0.4300938005592496,\n", - " \"Frlm_rlnu\": 327.71865443425077,\n", - " \"Frlm_rlnu_norm\": 0.5010988599912091,\n", - " \"Frlm_r_perc\": 0.6798336798336798,\n", - " \"Frlm_gl_var\": 3.4790211261678317,\n", - " \"Frlm_rl_var\": 0.5977798352177611,\n", - " \"Frlm_rl_entr\": 2.624426645711054\n", - " }\n", - " },\n", - " \"glszm_3D\": {\n", - " \"scale2_algoFBN_bin32\": {\n", - " \"Fszm_sze\": 0.25518204081632656,\n", - " \"Fszm_lze\": 550.0,\n", - " \"Fszm_lgze\": 0.25277777777777777,\n", - " \"Fszm_hgze\": 15.600000000000001,\n", - " \"Fszm_szlge\": 0.025604376417233562,\n", - " \"Fszm_szhge\": 2.7633453061224493,\n", - " \"Fszm_lzlge\": 502.7944444444445,\n", - " \"Fszm_lzhge\": 1494.6,\n", - " \"Fszm_glnu\": 1.4000000000000001,\n", - " \"Fszm_glnu_norm\": 0.28,\n", - " \"Fszm_zsnu\": 1.0000000000000002,\n", - " \"Fszm_zsnu_norm\": 0.20000000000000004,\n", - " \"Fszm_z_perc\": 0.06756756756756756,\n", - " \"Fszm_gl_var\": 2.6399999999999997,\n", - " \"Fszm_zs_var\": 330.9600000000001,\n", - " \"Fszm_zs_entr\": 2.321928094887362\n", - " }\n", - " },\n", - " \"gldzm_3D\": {\n", - " \"scale2_algoFBN_bin32\": {\n", - " \"Fdzm_sde\": 1.0,\n", - " \"Fdzm_lde\": 1.0,\n", - " \"Fdzm_lgze\": 0.25277777777777777,\n", - " \"Fdzm_hgze\": 15.600000000000001,\n", - " \"Fdzm_sdlge\": 0.25277777777777777,\n", - " \"Fdzm_sdhge\": 15.600000000000001,\n", - " \"Fdzm_ldlge\": 0.25277777777777777,\n", - " \"Fdzm_ldhge\": 15.600000000000001,\n", - " \"Fdzm_glnu\": 1.4000000000000001,\n", - " \"Fdzm_glnu_norm\": 0.28,\n", - " \"Fdzm_zdnu\": 5.0,\n", - " \"Fdzm_zdnu_norm\": 1.0,\n", - " \"Fdzm_z_perc\": 0.06756756756756757,\n", - " \"Fdzm_gl_var\": 2.6399999999999997,\n", - " \"Fdzm_zd_var\": 0.0,\n", - " \"Fdzm_zd_entr\": 1.9219280948873623\n", - " }\n", - " },\n", - " \"ngtdm_3D\": {\n", - " \"scale2_algoFBN_bin32\": {\n", - " \"Fngt_coarseness\": 0.029604225700771966,\n", - " \"Fngt_contrast\": 0.5837109155843376,\n", - " \"Fngt_busyness\": 6.543568456913214,\n", - " \"Fngt_complexity\": 13.539763601407845,\n", - " \"Fngt_strength\": 0.7634954330521357\n", - " }\n", - " },\n", - " \"ngldm_3D\": {\n", - " \"scale2_algoFBN_bin32\": {\n", - " \"Fngl_lde\": 0.044996357059631426,\n", - " \"Fngl_hde\": 109.0,\n", - " \"Fngl_lgce\": 0.6933183183183184,\n", - " \"Fngl_hgce\": 7.662162162162162,\n", - " \"Fngl_ldlge\": 0.00963060759417958,\n", - " \"Fngl_ldhge\": 0.7361715884134342,\n", - " \"Fngl_hdlge\": 102.45082582582583,\n", - " \"Fngl_hdhge\": 234.98648648648648,\n", - " \"Fngl_glnu\": 37.91891891891892,\n", - " \"Fngl_glnu_norm\": 0.512417823228634,\n", - " \"Fngl_dcnu\": 4.864864864864865,\n", - " \"Fngl_dcnu_norm\": 0.06574141709276844,\n", - " \"Fngl_gl_var\": 3.045471146822498,\n", - " \"Fngl_dc_var\": 22.056975894813732,\n", - " \"Fngl_dc_entr\": 4.403738379915684,\n", - " \"Fngl_dc_energy\": 0.053323593864134405\n", - " }\n", - " }\n", - " }\n", - "}\n" - ] - } - ], + "outputs": [], "source": [ "from numpyencoder import NumpyEncoder\n", "from json import dumps\n", @@ -903,9 +622,9 @@ ], "metadata": { "kernelspec": { - "display_name": "medimage", - "language": "python", - "name": "medimage" + "display_name": "Python 3 (ipykernel)", + "language": "mediml", + "name": "mediml" }, "language_info": { "codemirror_mode": { @@ -917,7 +636,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.13" + "version": "3.9.18" } }, "nbformat": 4, diff --git a/notebooks/ibsi/ibsi1p2.ipynb b/notebooks/ibsi/ibsi1p2.ipynb index 65e6bc3..b56bfed 100644 --- a/notebooks/ibsi/ibsi1p2.ipynb +++ b/notebooks/ibsi/ibsi1p2.ipynb @@ -8,9 +8,7 @@ "## IBSI Chapter 1 Phase 2 − Radiomic Computations\n", "\n", "@Author : [MEDomics consortium](https://github.com/medomics/)\n", - "\n", "@EMAIL : medomics.info@gmail.com\n", - "\n", "@REF : [IBSI 1](https://arxiv.org/pdf/1612.07003.pdf)" ] }, @@ -32,7 +30,7 @@ "source": [ "### Introduction\n", "\n", - "We recommend to take a look at the [MEDscan-tutorial notebook](https://colab.research.google.com/github/MahdiAll99/MEDimage/blob/dev/notebooks/tutorial/MEDscan-Tutorial.ipynb) and the [DataManager-tutorial](https://colab.research.google.com/github/MahdiAll99/MEDimage/blob/dev/notebooks/tutorial/DataManager-Tutorial.ipynb) before running the IBSI tests.\n", + "We recommend to take a look at the [MEDscan-tutorial notebook](https://colab.research.google.com/github/MEDomicsLab/MEDiml/blob/dev/notebooks/tutorial/MEDscan-Tutorial.ipynb) and the [DataManager-tutorial](https://colab.research.google.com/github/MEDomicsLab/MEDiml/blob/dev/notebooks/tutorial/DataManager-Tutorial.ipynb) before running the IBSI tests.\n", "\n", "In this notebook we treat the second phase where we focus on the standardization of image processing and feature computation. In the figure below, we focus on the second part, phase 2 where we compute radiomics features from a CT image after certain processing.\n", "\n", @@ -44,8 +42,14 @@ "id": "f7e50565", "metadata": {}, "source": [ + "#### ⚠️ DOWNLOADING THE CT IMAGES IS REQUIRED ⚠️\n", + "\n", "### Dataset - CT image\n", - "In this chapter and in this phase, reference values for features were obtained using a CT image, which is described below. The CT image can be found here: [IBSI 1 CT Phantom](https://github.com/theibsi/data_sets/tree/master/ibsi_1_ct_radiomics_phantom/dicom)" + "In this chapter and in this phase, reference values for features were obtained using a CT image, which is described below. The CT image can be found here: [IBSI 1 CT Phantom](https://github.com/theibsi/data_sets/tree/master/ibsi_1_ct_radiomics_phantom/dicom)\n", + "\n", + "**Please place the phantom in the following path: \"*notebooks/ibsi/data/CTimage*\"**\n", + "\n", + "We recommend using the following tool to download data from GitHub: https://download-directory.github.io/" ] }, { @@ -70,7 +74,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "PyCUDA is not installed. Please install it to use the textural filters.\n" + "PyCUDA is not installed. Please install it to use the textural filters. No module named 'pycuda'\n" ] } ], @@ -81,7 +85,7 @@ "from copy import deepcopy\n", "from pathlib import Path\n", "\n", - "import MEDimage" + "import MEDiml" ] }, { @@ -130,18 +134,6 @@ "So the first step is to initialize the ``MEDscan`` class using the ``DataManager``. This class will only need path to where the data is located (either DICOM or NIfTI). We will use DICOM for now." ] }, - { - "cell_type": "markdown", - "id": "033e323c", - "metadata": {}, - "source": [ - "Make sure your folder structure looks like this:\n", - "\n", - "\n", - "\n", - "Make sure to also download the [CT-Image data](https://github.com/theibsi/data_sets/tree/master/ibsi_1_ct_radiomics_phantom/dicom) (DICOM files) and place it in CTimage folder. The settings file can be found in the repository and is automatically place in the settings folder." - ] - }, { "cell_type": "markdown", "id": "63ee7477", @@ -162,7 +154,7 @@ "path_settings = Path(os.getcwd()) / \"settings\" # Path to the script settings/configuration folder\n", "\n", "# Load script parameters\n", - "im_params = MEDimage.utils.json_utils.load_json(path_settings / f'Phase2{CONFIG}_settings.json')" + "im_params = MEDiml.utils.json_utils.load_json(path_settings / f'Phase2{CONFIG}_settings.json')" ] }, { @@ -178,14 +170,87 @@ "execution_count": 4, "id": "1dbb7ba8", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-02-04 10:12:17,663\tINFO worker.py:2003 -- Started a local Ray instance. View the dashboard at \u001b[1m\u001b[32m127.0.0.1:8265 \u001b[39m\u001b[22m\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--> Reading all DICOM objects to create MEDscan classes\n", + "\n", + "--> Scanning all folders in initial directory..." + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████████████████████████████████████████████████████████████████████████████| 61/61 [00:00<00:00, 64.96it/s]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "DONE\n", + "--> Associating all RT objects to imaging volumes\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00 Processing DICOMs and creating MEDscan objects\n", + ":job_id:01000000\n", + ":task_name:process_files_wrapper\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:root:The patient ID of the following file: 1__CT.CTscan.npy does not respect the MEDiml naming convention 'study-institution-id' (Ex: Glioma-TCGA-001)\n", + "100%|██████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 1000.31it/s]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "DONE\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], "source": [ "# Intialize the DataManager class\n", "path_to_dicoms = Path(os.getcwd()) / \"data\" / \"CTimage\"\n", - "dm = MEDimage.wrangling.DataManager(path_to_dicoms=path_to_dicoms, path_save=path_to_dicoms, save=True)\n", + "dm = MEDiml.wrangling.DataManager(path_to_dicoms=path_to_dicoms, path_save=path_to_dicoms, save=True)\n", "\n", "# Process the DICOM scan\n", - "#dm.process_all_dicoms()\n", + "dm.process_all_dicoms()\n", "\n", "# Load the scan\n", "import pickle\n", @@ -231,7 +296,7 @@ "metadata": {}, "outputs": [], "source": [ - "vol_obj_init, roi_obj_init = MEDimage.processing.get_roi_from_indexes(MEDinstance,\n", + "vol_obj_init, roi_obj_init = MEDiml.processing.get_roi_from_indexes(MEDinstance,\n", " name_roi='{GTV-1}',\n", " box_string='full')" ] @@ -270,7 +335,7 @@ "outputs": [], "source": [ "# intial diagnostic features extraction:\n", - "diag_initial = MEDimage.biomarkers.diagnostics.extract_all(\n", + "diag_initial = MEDiml.biomarkers.diagnostics.extract_all(\n", " vol_obj_init, \n", " roi_obj_init, \n", " roi_obj_init, \n", @@ -334,7 +399,7 @@ "\n", "if CONFIG != 'A':\n", " # Intensity Mask\n", - " vol_obj = MEDimage.processing.interp_volume(\n", + " vol_obj = MEDiml.processing.interp_volume(\n", " medscan=MEDinstance,\n", " vol_obj_s=vol_obj_init,\n", " roi_obj_s=roi_obj_init,\n", @@ -342,7 +407,7 @@ " box_string='full'\n", " )\n", " # Morphological Mask\n", - " roi_obj_morph = MEDimage.processing.interp_volume(\n", + " roi_obj_morph = MEDiml.processing.interp_volume(\n", " medscan=MEDinstance,\n", " vol_obj_s=roi_obj_init,\n", " roi_obj_s=roi_obj_init,\n", @@ -407,7 +472,7 @@ "outputs": [], "source": [ "# Post-interpolation diagnostic features extraction:\n", - "diag_interp = MEDimage.biomarkers.diagnostics.extract_all(vol_obj, roi_obj_morph, roi_obj_morph, 'interp')\n", + "diag_interp = MEDiml.biomarkers.diagnostics.extract_all(vol_obj, roi_obj_morph, roi_obj_morph, 'interp')\n", "\n", "# Update diagnostic Dict:\n", "MEDinstance.radiomics.image.update(\n", @@ -452,7 +517,7 @@ "# Intensity mask re-segmentation\n", "roi_obj_int = deepcopy(roi_obj_morph)\n", "\n", - "roi_obj_int.data = MEDimage.processing.range_re_seg(\n", + "roi_obj_int.data = MEDiml.processing.range_re_seg(\n", " vol=vol_obj.data, \n", " roi=roi_obj_int.data,\n", " im_range=MEDinstance.params.process.im_range\n", @@ -492,7 +557,7 @@ "outlier_range = [u + 3*sigma, u - 3*sigma]\n", "\n", "# Intensity mask outlier re-segmentation\n", - "roi_obj_int.data = np.logical_and(MEDimage.processing.outlier_re_seg(\n", + "roi_obj_int.data = np.logical_and(MEDiml.processing.outlier_re_seg(\n", " vol=vol_obj.data, \n", " roi=roi_obj_int.data, \n", " outliers=MEDinstance.params.process.outliers),\n", @@ -516,7 +581,7 @@ "outputs": [], "source": [ "# Post-resegmentation diagnostic features extraction:\n", - "diag_re_seg = MEDimage.biomarkers.diagnostics.extract_all(vol_obj, roi_obj_int, roi_obj_morph, 'reSeg')\n", + "diag_re_seg = MEDiml.biomarkers.diagnostics.extract_all(vol_obj, roi_obj_int, roi_obj_morph, 'reSeg')\n", "\n", "# Update diagnostic Dict:\n", "MEDinstance.radiomics.image.update(\n", @@ -544,7 +609,7 @@ "metadata": {}, "outputs": [], "source": [ - "vol_int_re = MEDimage.processing.roi_extract(\n", + "vol_int_re = MEDiml.processing.roi_extract(\n", " vol=vol_obj.data, \n", " roi=roi_obj_int.data\n", " )" @@ -638,7 +703,7 @@ "metadata": {}, "outputs": [], "source": [ - "morph = MEDimage.biomarkers.morph.extract_all(\n", + "morph = MEDiml.biomarkers.morph.extract_all(\n", " vol=vol_obj.data, \n", " mask_int=roi_obj_int.data, \n", " mask_morph=roi_obj_morph.data,\n", @@ -665,7 +730,7 @@ "metadata": {}, "outputs": [], "source": [ - "local_intensity = MEDimage.biomarkers.local_intensity.extract_all(\n", + "local_intensity = MEDiml.biomarkers.local_intensity.extract_all(\n", " img_obj=vol_obj.data,\n", " roi_obj=roi_obj_int.data,\n", " res=MEDinstance.params.process.scale_non_text,\n", @@ -692,7 +757,7 @@ "metadata": {}, "outputs": [], "source": [ - "stats = MEDimage.biomarkers.stats.extract_all(vol=vol_int_re, intensity_type=\"definite\")" + "stats = MEDiml.biomarkers.stats.extract_all(vol=vol_int_re, intensity_type=\"definite\")" ] }, { @@ -720,7 +785,7 @@ "metadata": {}, "outputs": [], "source": [ - "vol_quant_re, _ = MEDimage.processing.discretisation.discretize(\n", + "vol_quant_re, _ = MEDiml.processing.discretisation.discretize(\n", " vol_re=vol_int_re,\n", " discr_type=MEDinstance.params.process.ih['type'], \n", " n_q=MEDinstance.params.process.ih['val'], \n", @@ -746,7 +811,7 @@ "metadata": {}, "outputs": [], "source": [ - "int_hist = MEDimage.biomarkers.intensity_histogram.extract_all(\n", + "int_hist = MEDiml.biomarkers.intensity_histogram.extract_all(\n", " vol=vol_quant_re\n", " )" ] @@ -774,7 +839,7 @@ "source": [ "if MEDinstance.params.process.ivh and 'type' in MEDinstance.params.process.ivh and 'val' in MEDinstance.params.process.ivh:\n", " if MEDinstance.params.process.ivh['type'] and MEDinstance.params.process.ivh['val']:\n", - " vol_quant_re, wd = MEDimage.processing.discretize(\n", + " vol_quant_re, wd = MEDiml.processing.discretize(\n", " vol_re=vol_int_re,\n", " discr_type=MEDinstance.params.process.ivh['type'], \n", " n_q=MEDinstance.params.process.ivh['val'], \n", @@ -801,7 +866,7 @@ "metadata": {}, "outputs": [], "source": [ - "int_vol_hist = MEDimage.biomarkers.int_vol_hist.extract_all(\n", + "int_vol_hist = MEDiml.biomarkers.int_vol_hist.extract_all(\n", " medscan=MEDinstance,\n", " vol=vol_quant_re,\n", " vol_int_re=vol_int_re, \n", @@ -847,7 +912,7 @@ "for s in range(MEDinstance.params.process.n_scale):\n", " # Interpolation\n", " # Intensity Mask\n", - " vol_obj = MEDimage.processing.interp_volume(\n", + " vol_obj = MEDiml.processing.interp_volume(\n", " medscan=MEDinstance,\n", " vol_obj_s=vol_obj_init,\n", " vox_dim=MEDinstance.params.process.scale_text[s],\n", @@ -858,7 +923,7 @@ " box_string=MEDinstance.params.process.box_string\n", " )\n", " # Morphological Mask\n", - " roi_obj_morph = MEDimage.processing.interp_volume(\n", + " roi_obj_morph = MEDiml.processing.interp_volume(\n", " medscan=MEDinstance,\n", " vol_obj_s=roi_obj_init,\n", " vox_dim=MEDinstance.params.process.scale_text[s],\n", @@ -872,14 +937,14 @@ " # Re-segmentation\n", " # Intensity mask range re-segmentation\n", " roi_obj_int = deepcopy(roi_obj_morph)\n", - " roi_obj_int.data = MEDimage.processing.range_re_seg(\n", + " roi_obj_int.data = MEDiml.processing.range_re_seg(\n", " vol=vol_obj.data, \n", " roi=roi_obj_int.data,\n", " im_range=MEDinstance.params.process.im_range\n", " )\n", " # Intensity mask outlier re-segmentation\n", " roi_obj_int.data = np.logical_and(\n", - " MEDimage.processing.outlier_re_seg(\n", + " MEDiml.processing.outlier_re_seg(\n", " vol=vol_obj.data, \n", " roi=roi_obj_int.data, \n", " outliers=MEDinstance.params.process.outliers\n", @@ -894,12 +959,12 @@ " MEDinstance.init_tf_calculation(algo=a, gl=n, scale=s)\n", "\n", " # ROI Extraction :\n", - " vol_int_re = MEDimage.processing.roi_extract(\n", + " vol_int_re = MEDiml.processing.roi_extract(\n", " vol=vol_obj.data, \n", " roi=roi_obj_int.data)\n", "\n", " # Discretisation :\n", - " vol_quant_re, _ = MEDimage.processing.discretize(\n", + " vol_quant_re, _ = MEDiml.processing.discretize(\n", " vol_re=vol_int_re,\n", " discr_type=MEDinstance.params.process.algo[a], \n", " n_q=MEDinstance.params.process.gray_levels[a][n], \n", @@ -907,31 +972,31 @@ " )\n", "\n", " # GLCM features extraction\n", - " glcm = MEDimage.biomarkers.glcm.extract_all(\n", + " glcm = MEDiml.biomarkers.glcm.extract_all(\n", " vol=vol_quant_re, \n", " dist_correction=MEDinstance.params.radiomics.glcm.dist_correction)\n", "\n", " # GLRLM features extraction\n", - " glrlm = MEDimage.biomarkers.glrlm.extract_all(\n", + " glrlm = MEDiml.biomarkers.glrlm.extract_all(\n", " vol=vol_quant_re,\n", " dist_correction=MEDinstance.params.radiomics.glrlm.dist_correction)\n", "\n", " # GLSZM features extraction\n", - " glszm = MEDimage.biomarkers.glszm.extract_all(\n", + " glszm = MEDiml.biomarkers.glszm.extract_all(\n", " vol=vol_quant_re)\n", "\n", " # GLDZM features extraction\n", - " gldzm = MEDimage.biomarkers.gldzm.extract_all(\n", + " gldzm = MEDiml.biomarkers.gldzm.extract_all(\n", " vol_int=vol_quant_re, \n", " mask_morph=roi_obj_morph.data)\n", "\n", " # NGTDM features extraction\n", - " ngtdm = MEDimage.biomarkers.ngtdm.extract_all(\n", + " ngtdm = MEDiml.biomarkers.ngtdm.extract_all(\n", " vol=vol_quant_re, \n", " dist_correction=MEDinstance.params.radiomics.ngtdm.dist_correction)\n", "\n", " # NGLDM features extraction\n", - " ngldm = MEDimage.biomarkers.ngldm.extract_all(\n", + " ngldm = MEDiml.biomarkers.ngldm.extract_all(\n", " vol=vol_quant_re)\n", "\n", " # Update radiomics results class\n", @@ -1054,19 +1119,19 @@ " \"Fmorph_asphericity\": 0.3827698125933494,\n", " \"Fmorph_com\": 68.53997705762669,\n", " \"Fmorph_diam\": 125.05998560690786,\n", - " \"Fmorph_pca_major\": 93.27035347558969,\n", - " \"Fmorph_pca_minor\": 82.00519180391295,\n", + " \"Fmorph_pca_major\": 93.27035347558972,\n", + " \"Fmorph_pca_minor\": 82.00519180391296,\n", " \"Fmorph_pca_least\": 70.90152846941119,\n", - " \"Fmorph_pca_elongation\": 0.879220339026323,\n", - " \"Fmorph_pca_flatness\": 0.7601721857735559,\n", + " \"Fmorph_pca_elongation\": 0.8792203390263229,\n", + " \"Fmorph_pca_flatness\": 0.7601721857735557,\n", " \"Fmorph_v_dens_aabb\": 0.47826296334860474,\n", " \"Fmorph_a_dens_aabb\": 0.6784182092917099,\n", " \"Fmorph_v_dens_ombb\": 0.4920510501195718,\n", " \"Fmorph_a_dens_ombb\": 0.6918245430188453,\n", - " \"Fmorph_v_dens_aee\": 1.2941055431955213,\n", - " \"Fmorph_a_dens_aee\": 1.6167546557562238,\n", - " \"Fmorph_v_dens_mvee\": 0.3233816243947214,\n", - " \"Fmorph_a_dens_mvee\": 0.6181651987893297,\n", + " \"Fmorph_v_dens_aee\": 1.2941055431955208,\n", + " \"Fmorph_a_dens_aee\": 1.6167546557562233,\n", + " \"Fmorph_v_dens_mvee\": 0.32338162439471596,\n", + " \"Fmorph_a_dens_mvee\": 0.6181651987893154,\n", " \"Fmorph_v_dens_conv_hull\": 0.8336688547401527,\n", " \"Fmorph_a_dens_conv_hull\": 1.1301335281187814,\n", " \"Fmorph_integ_int\": -8314028.309137344,\n", @@ -1130,7 +1195,7 @@ " }\n", " },\n", " \"intVolHist_3D\": {\n", - " \"scale2_algoFBN_bin1000\": {\n", + " \"scale2_algoFBN_bin1000_minM1000_max400\": {\n", " \"Fivh_V10\": 0.9745526481431526,\n", " \"Fivh_V90\": 0.0001573599496448308,\n", " \"Fivh_I10\": 770.0,\n", @@ -1192,9 +1257,9 @@ " },\n", " \"glszm_3D\": {\n", " \"scale2_algoFBN_bin32\": {\n", - " \"Fszm_sze\": 0.676399479482647,\n", + " \"Fszm_sze\": 0.6763994794826471,\n", " \"Fszm_lze\": 58563.98497047772,\n", - " \"Fszm_lgze\": 0.03400006559226447,\n", + " \"Fszm_lgze\": 0.034000065592264476,\n", " \"Fszm_hgze\": 285.8554303095366,\n", " \"Fszm_szlge\": 0.0224346411463456,\n", " \"Fszm_szhge\": 186.01602296949463,\n", @@ -1212,7 +1277,7 @@ " },\n", " \"gldzm_3D\": {\n", " \"scale2_algoFBN_bin32\": {\n", - " \"Fdzm_sde\": 0.5268698697360265,\n", + " \"Fdzm_sde\": 0.5268698697360263,\n", " \"Fdzm_lde\": 12.566648774378244,\n", " \"Fdzm_lgze\": 0.034000065592264476,\n", " \"Fdzm_hgze\": 285.8554303095366,\n", @@ -1282,9 +1347,9 @@ ], "metadata": { "kernelspec": { - "display_name": "medimage", + "display_name": "mediml", "language": "python", - "name": "medimage" + "name": "mediml" }, "language_info": { "codemirror_mode": { @@ -1296,7 +1361,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.13" + "version": "3.9.18" } }, "nbformat": 4, diff --git a/notebooks/ibsi/ibsi2p1.ipynb b/notebooks/ibsi/ibsi2p1.ipynb index bb2e12a..2512bcd 100644 --- a/notebooks/ibsi/ibsi2p1.ipynb +++ b/notebooks/ibsi/ibsi2p1.ipynb @@ -10,9 +10,7 @@ "### Technical validation of image filters without additional image processing\n", "\n", "@Author : [MEDomics consortium](https://github.com/medomics/)\n", - "\n", "@EMAIL : medomics.info@gmail.com\n", - "\n", "@REF : [IBSI 2](https://www.overleaf.com/read/hwhjswzkhwdh)" ] }, @@ -42,7 +40,7 @@ "source": [ "### Introduction\n", "\n", - "We recommend to take a look at the [MEDscan-tutorial notebook](https://colab.research.google.com/github/MahdiAll99/MEDimage/blob/dev/notebooks/tutorial/MEDscan-Tutorial.ipynb) and the [DataManager-tutorial](https://colab.research.google.com/github/MahdiAll99/MEDimage/blob/dev/notebooks/tutorial/DataManager-Tutorial.ipynb) before running the IBSI tests.\n", + "We recommend to take a look at the [MEDscan-tutorial notebook](https://colab.research.google.com/github/MEDomicsLab/MEDiml/blob/dev/notebooks/tutorial/MEDscan-Tutorial.ipynb) and the [DataManager-tutorial](https://colab.research.google.com/github/MEDomicsLab/MEDiml/blob/dev/notebooks/tutorial/DataManager-Tutorial.ipynb) before running the IBSI tests.\n", "\n", "The aim of this chapter and this phase is benchmarking the filters using the phantom images is to arrive at a standard implementation. We apply filter to the phantoms to create a response maps with the same dimensions as the phantoms (64 × 64 × 64 voxels). Filters need to be applied using the settings provided in [IBSI 2 benchmarking 5.1 Table 5.1](https://www.overleaf.com/read/hwhjswzkhwdh). In this notebook we implemented 28 different settings/tests from ***1a1*** to ***7a2***." ] @@ -69,9 +67,13 @@ "source": [ "### Initialization\n", "\n", - "In this chapter and phase we will not need any class and we will use the *MEDimage* package modules directly, especially the module ``filter`` which offers methods for image filtering. We recommend you download the data from [here](https://github.com/theibsi/data_sets/tree/master/ibsi_2_digital_phantom/nifti) and organize your folder as follows:\n", + "In this chapter and phase we will not need any class and we will use the *MEDimage* package modules directly, especially the module ``filter`` which offers methods for image filtering. \n", + "\n", + "#### ⚠️ DOWNLOADING THE DATA IS REQUIRED ⚠️\n", + "\n", + "You can download the data from [HERE](https://github.com/theibsi/data_sets/tree/master/ibsi_2_digital_phantom/nifti). We recommend using the following tool to download data from GitHub: https://download-directory.github.io/\n", "\n", - "\n" + "**Please place the data in the following path: \"*notebooks/ibsi/data/filters*\"**\n" ] }, { @@ -84,7 +86,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "PyCUDA is not installed. Please install it to use the textural filters.\n" + "PyCUDA is not installed. Please install it to use the textural filters. No module named 'pycuda'\n" ] } ], @@ -98,9 +100,10 @@ "import numpy as np\n", "from matplotlib.cm import ScalarMappable\n", "from matplotlib.colors import Normalize\n", + "from pathlib import Path\n", "\n", "\n", - "import MEDimage\n", + "import MEDiml\n", "import numpy as np" ] }, @@ -181,7 +184,7 @@ "metadata": {}, "outputs": [], "source": [ - "def get_input(image_name, repertory=\"data/Filters\"):\n", + "def get_input(image_name):\n", " \"\"\"\n", " Import the nii image and cast it into numpy nd-array.\n", " :param image_name: The image name without the extension.\n", @@ -189,13 +192,16 @@ " :return: a numpy nd-array of shape (B, W, H, D) with value between 0 and 1.\n", " \"\"\"\n", "\n", - " example_filename = os.path.join(\n", - " repertory, image_name + '.nii'\n", - " )\n", + " example_filename = [file for file in list((Path.cwd() / \"data/filters\").rglob('*.nii*')) if image_name in file.name]\n", + " \n", + " if len(example_filename) == 0: raise ValueError(f\"File {image_name} not found\")\n", + " \n", + " example_filename = example_filename[0]\n", + " \n", " try:\n", " input_data = nib.load(example_filename)\n", - " except:\n", - " input_data = nib.load(example_filename+'.gz')\n", + " except Exception as e:\n", + " raise ValueError(f\"Error occured while loading {image_name}: {e}\")\n", "\n", " input_data.set_data_dtype(np.float64)\n", "\n", @@ -223,7 +229,7 @@ " vmin = np.min(result)\n", " vmax = np.max(result)\n", "\n", - " fig.suptitle(f'Filter used : {filter_name}.\\nResult\\'s min : {vmin} Result\\'s max : {vmax}',\n", + " fig.suptitle(f'Filter used : {filter_name}.\\nResult\\'s min : {round(vmin, 4)} Result\\'s max : {round(vmax, 4)}',\n", " fontsize=16)\n", "\n", " fig.add_subplot(1, 3, 1, ylabel=\"Result\")\n", @@ -308,7 +314,7 @@ "source": [ "if test_id == \"1a1\":\n", " input_images = get_input(\"checkerboard\")\n", - " result = MEDimage.filters.apply_mean(\n", + " result = MEDiml.filters.apply_mean(\n", " input_images=input_images,\n", " ndims=3,\n", " size=15, \n", @@ -317,7 +323,7 @@ "\n", "elif test_id == \"1a2\":\n", " input_images = get_input(\"checkerboard\")\n", - " result = MEDimage.filters.apply_mean(\n", + " result = MEDiml.filters.apply_mean(\n", " input_images=input_images,\n", " ndims=3,\n", " size=15, \n", @@ -326,7 +332,7 @@ "\n", "elif test_id == \"1a3\":\n", " input_images = get_input(\"checkerboard\")\n", - " result = MEDimage.filters.apply_mean(\n", + " result = MEDiml.filters.apply_mean(\n", " input_images=input_images,\n", " ndims=3,\n", " size=15, \n", @@ -335,7 +341,7 @@ "\n", "elif test_id == \"1a4\":\n", " input_images = get_input(\"checkerboard\")\n", - " result = MEDimage.filters.apply_mean(\n", + " result = MEDiml.filters.apply_mean(\n", " input_images=input_images,\n", " ndims=3,\n", " size=15, \n", @@ -344,7 +350,7 @@ "\n", "elif test_id == \"1b1\":\n", " input_images = get_input(\"response\")\n", - " result = MEDimage.filters.apply_mean(\n", + " result = MEDiml.filters.apply_mean(\n", " input_images=input_images,\n", " ndims=2,\n", " size=15, \n", @@ -353,7 +359,7 @@ "\n", "elif test_id == \"2a\":\n", " input_images = get_input(\"response\")\n", - " result = MEDimage.filters.apply_log(\n", + " result = MEDiml.filters.apply_log(\n", " input_images=input_images,\n", " ndims=3,\n", " voxel_length=VOLEX_LENGTH,\n", @@ -363,7 +369,7 @@ "\n", "elif test_id == \"2b\":\n", " input_images = get_input(\"checkerboard\")\n", - " result = MEDimage.filters.apply_log(\n", + " result = MEDiml.filters.apply_log(\n", " input_images=input_images,\n", " ndims=3,\n", " voxel_length=VOLEX_LENGTH,\n", @@ -373,7 +379,7 @@ "\n", "elif test_id == \"2c\":\n", " input_images = get_input(\"checkerboard\")\n", - " result = MEDimage.filters.apply_log(\n", + " result = MEDiml.filters.apply_log(\n", " input_images=input_images,\n", " ndims=2,\n", " voxel_length=VOLEX_LENGTH,\n", @@ -383,7 +389,7 @@ "\n", "elif test_id == \"3a1\":\n", " input_images = get_input(\"response\")\n", - " result = MEDimage.filters.apply_laws(\n", + " result = MEDiml.filters.apply_laws(\n", " input_images=input_images,\n", " config=[\"E5\", \"L5\", \"S5\"],\n", " padding=\"constant\")\n", @@ -391,7 +397,7 @@ "\n", "elif test_id == \"3a2\":\n", " input_images = get_input(\"response\")\n", - " result = MEDimage.filters.apply_laws(\n", + " result = MEDiml.filters.apply_laws(\n", " input_images=input_images,\n", " config=[\"E5\", \"L5\", \"S5\"],\n", " padding=\"constant\",\n", @@ -400,7 +406,7 @@ "\n", "elif test_id == \"3a3\":\n", " input_images = get_input(\"response\")\n", - " result = MEDimage.filters.apply_laws(\n", + " result = MEDiml.filters.apply_laws(\n", " input_images=input_images,\n", " config=[\"E5\", \"L5\", \"S5\"],\n", " padding=\"constant\",\n", @@ -410,7 +416,7 @@ "\n", "elif test_id == \"3b1\":\n", " input_images = get_input(\"checkerboard\")\n", - " result = MEDimage.filters.apply_laws(\n", + " result = MEDiml.filters.apply_laws(\n", " input_images=input_images,\n", " config=[\"E3\", \"W5\", \"R5\"],\n", " padding=\"symmetric\",\n", @@ -420,7 +426,7 @@ "\n", "elif test_id == \"3b2\":\n", " input_images = get_input(\"checkerboard\")\n", - " result = MEDimage.filters.apply_laws(\n", + " result = MEDiml.filters.apply_laws(\n", " input_images=input_images,\n", " config=[\"E3\", \"W5\", \"R5\"],\n", " padding=\"symmetric\",\n", @@ -430,7 +436,7 @@ "\n", "elif test_id == \"3b3\":\n", " input_images = get_input(\"checkerboard\")\n", - " result = MEDimage.filters.apply_laws(\n", + " result = MEDiml.filters.apply_laws(\n", " input_images=input_images,\n", " config=[\"E3\", \"W5\", \"R5\"],\n", " padding=\"symmetric\",\n", @@ -440,7 +446,7 @@ "\n", "elif test_id == \"3c1\":\n", " input_images = get_input(\"checkerboard\")\n", - " result = MEDimage.filters.apply_laws(\n", + " result = MEDiml.filters.apply_laws(\n", " input_images=input_images,\n", " config=[\"L5\", \"S5\"],\n", " padding=\"symmetric\",\n", @@ -450,7 +456,7 @@ "\n", "elif test_id == \"3c2\":\n", " input_images = get_input(\"checkerboard\")\n", - " result = MEDimage.filters.apply_laws(\n", + " result = MEDiml.filters.apply_laws(\n", " input_images=input_images,\n", " config=[\"L5\", \"S5\"],\n", " padding=\"symmetric\",\n", @@ -460,7 +466,7 @@ " \n", "elif test_id == \"3c3\":\n", " input_images = get_input(\"checkerboard\")\n", - " result = MEDimage.filters.apply_laws(\n", + " result = MEDiml.filters.apply_laws(\n", " input_images=input_images,\n", " config=[\"L5\", \"S5\"],\n", " padding=\"symmetric\",\n", @@ -470,7 +476,7 @@ "\n", "elif test_id == \"4a1\":\n", " input_images = get_input(\"response\")\n", - " result = MEDimage.filters.apply_gabor(\n", + " result = MEDiml.filters.apply_gabor(\n", " input_images=input_images,\n", " voxel_length=VOLEX_LENGTH,\n", " sigma=10,\n", @@ -484,7 +490,7 @@ "\n", "elif test_id == \"4a2\":\n", " input_images = get_input(\"response\")\n", - " result = MEDimage.filters.apply_gabor(\n", + " result = MEDiml.filters.apply_gabor(\n", " input_images=input_images,\n", " voxel_length=VOLEX_LENGTH,\n", " sigma=10,\n", @@ -498,7 +504,7 @@ "\n", "elif test_id == \"4b1\":\n", " input_images = get_input(\"sphere\")\n", - " result = MEDimage.filters.apply_gabor(\n", + " result = MEDiml.filters.apply_gabor(\n", " input_images=input_images,\n", " voxel_length=VOLEX_LENGTH,\n", " sigma=20,\n", @@ -513,7 +519,7 @@ "\n", "elif test_id == \"4b2\":\n", " input_images = get_input(\"sphere\")\n", - " result = MEDimage.filters.apply_gabor(\n", + " result = MEDiml.filters.apply_gabor(\n", " input_images=input_images,\n", " voxel_length=VOLEX_LENGTH,\n", " sigma=20,\n", @@ -527,7 +533,7 @@ "\n", "elif test_id == \"5a1\":\n", " input_images = get_input(\"response\")\n", - " result = MEDimage.filters.apply_wavelet(\n", + " result = MEDiml.filters.apply_wavelet(\n", " input_images=input_images,\n", " ndims=3,\n", " wavelet_name=\"db2\",\n", @@ -539,7 +545,7 @@ "\n", "elif test_id == \"5a2\":\n", " input_images = get_input(\"response\")\n", - " result = MEDimage.filters.apply_wavelet(\n", + " result = MEDiml.filters.apply_wavelet(\n", " input_images=input_images,\n", " ndims=3,\n", " wavelet_name=\"db2\",\n", @@ -551,7 +557,7 @@ "\n", "elif test_id == \"6a1\":\n", " input_images = get_input(\"sphere\")\n", - " result = MEDimage.filters.apply_wavelet(\n", + " result = MEDiml.filters.apply_wavelet(\n", " input_images=input_images,\n", " ndims=3,\n", " wavelet_name=\"coif1\",\n", @@ -563,7 +569,7 @@ "\n", "elif test_id == \"6a2\":\n", " input_images = get_input(\"sphere\")\n", - " result = MEDimage.filters.apply_wavelet(\n", + " result = MEDiml.filters.apply_wavelet(\n", " input_images=input_images,\n", " ndims=3,\n", " wavelet_name=\"coif1\",\n", @@ -575,7 +581,7 @@ "\n", "elif test_id == \"7a1\":\n", " input_images = get_input(\"checkerboard\")\n", - " result = MEDimage.filters.apply_wavelet(\n", + " result = MEDiml.filters.apply_wavelet(\n", " input_images=input_images,\n", " ndims=3,\n", " wavelet_name=\"haar\",\n", @@ -587,7 +593,7 @@ "\n", "elif test_id == \"7a2\":\n", " input_images = get_input(\"checkerboard\")\n", - " result = MEDimage.filters.apply_wavelet(\n", + " result = MEDiml.filters.apply_wavelet(\n", " input_images=input_images,\n", " ndims=3,\n", " wavelet_name=\"haar\",\n", @@ -616,7 +622,7 @@ "outputs": [ { "data": { - "image/png": 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" ] @@ -643,9 +649,9 @@ ], "metadata": { "kernelspec": { - "display_name": "medimage", + "display_name": "mediml", "language": "python", - "name": "medimage" + "name": "mediml" }, "language_info": { "codemirror_mode": { @@ -657,7 +663,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.13" + "version": "3.9.18" } }, "nbformat": 4, diff --git a/notebooks/ibsi/ibsi2p2.ipynb b/notebooks/ibsi/ibsi2p2.ipynb index 114a4b7..c260453 100644 --- a/notebooks/ibsi/ibsi2p2.ipynb +++ b/notebooks/ibsi/ibsi2p2.ipynb @@ -32,9 +32,9 @@ "source": [ "### Introduction\n", "\n", - "We recommend to take a look at the [MEDscan-tutorial notebook](https://colab.research.google.com/github/MahdiAll99/MEDimage/blob/dev/notebooks/tutorial/MEDscan-Tutorial.ipynb) and the [DataManager-tutorial](https://colab.research.google.com/github/MahdiAll99/MEDimage/blob/dev/notebooks/tutorial/DataManager-Tutorial.ipynb) before running the IBSI tests.\n", + "We recommend to take a look at the [MEDscan-tutorial notebook](https://colab.research.google.com/github/MEDomicsLab/MEDiml/blob/dev/notebooks/tutorial/MEDscan-Tutorial.ipynb) and the [DataManager-tutorial](https://colab.research.google.com/github/MEDomicsLab/MEDiml/blob/dev/notebooks/tutorial/DataManager-Tutorial.ipynb) before running the IBSI tests.\n", "\n", - "The aim of this chapter and this phase is to extract filter-based radiomics features from the same CT-image mentionned in chapter 1. The methodology used to extract these values is described in [IBSI 2 benchmarking 5.2](https://www.overleaf.com/project/5da9e0b82f399f0001ad3970). As shows the figure below, the IBSI chapter 2 gives 2 configurations to test for image processing : configuration *A* and *B* and we will only test configuration *A* since *MEDimage Package* does not implement 2D feature computation.\n", + "The aim of this chapter and this phase is to extract filter-based radiomics features from the same CT-image mentionned in chapter 1. The methodology used to extract these values is described in [IBSI 2 benchmarking 5.2](https://www.overleaf.com/project/5da9e0b82f399f0001ad3970). As shows the figure below, the IBSI chapter 2 gives 2 configurations to test for image processing : configuration *A* and *B* and we will only test configuration *A* since *MEDiml Package* does not implement 2D feature computation.\n", "\n", "\n", "\"Flowchart\n" @@ -42,11 +42,17 @@ }, { "cell_type": "markdown", - "id": "f7e50565", + "id": "8d1f17ff-cdcc-4b78-9de7-a958c57af21d", "metadata": {}, "source": [ + "#### ⚠️ DOWNLOADING THE DATA IS REQUIRED (IF NOT DONE IN IBSI1P2) ⚠️\n", + "\n", "### Dataset - CT image\n", - "We use the same CT image as in IBSI 1 phase 2. The image can be found here: [ibsi_1_ct_radiomics_phantom](https://github.com/theibsi/data_sets/tree/master/ibsi_1_ct_radiomics_phantom)" + "The CT image required for this phase can be found here: [IBSI 1 CT Phantom](https://github.com/theibsi/data_sets/tree/master/ibsi_1_ct_radiomics_phantom/dicom)\n", + "\n", + "**Please place the phantom in the following path: \"*notebooks/ibsi/data/CTimage*\"**\n", + "\n", + "We recommend using the following tool to download data from GitHub: https://download-directory.github.io/" ] }, { @@ -59,7 +65,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "PyCUDA is not installed. Please install it to use the textural filters.\n" + "PyCUDA is not installed. Please install it to use the textural filters. No module named 'pycuda'\n" ] } ], @@ -70,7 +76,7 @@ "from copy import deepcopy\n", "from pathlib import Path\n", "\n", - "import MEDimage" + "import MEDiml" ] }, { @@ -113,32 +119,32 @@ " fig.suptitle(f'Original image vs Processed image using {filter_name}. (Test ID : {test_id}.B)', fontsize=16)\n", "\n", " fig.add_subplot(2, 3, 1, ylabel=\"Original image\", title=\"Coronal\")\n", - " plt.imshow(original_data[:, :, slice_nb], cmap='gray')\n", + " plt.imshow(original_data[:, :, slice_nb].T, cmap='gray')\n", "\n", " fig.add_subplot(2, 3, 2, title=\"Axial\")\n", - " plt.imshow(original_data[:, slice_nb, :], cmap='gray')\n", + " plt.imshow(original_data[:, slice_nb, :].T, cmap='gray')\n", "\n", " fig.add_subplot(2, 3, 3, title=\"Sagittal\")\n", - " plt.imshow(original_data[slice_nb, :, :], cmap='gray')\n", + " plt.imshow(original_data[slice_nb, :, :].T, cmap='gray')\n", "\n", " fig.add_subplot(2, 3, 4, ylabel=\"Result\")\n", - " plt.imshow(result[:, :, slice_nb], cmap='gray')\n", + " plt.imshow(result[:, :, slice_nb].T, cmap='gray')\n", "\n", " fig.add_subplot(2, 3, 5)\n", - " plt.imshow(result[:, slice_nb, :], cmap='gray')\n", + " plt.imshow(result[:, slice_nb, :].T, cmap='gray')\n", "\n", " fig.add_subplot(2, 3, 6)\n", - " plt.imshow(result[slice_nb, :, :], cmap='gray')\n", + " plt.imshow(result[slice_nb, :, :].T, cmap='gray')\n", "\n", " else:\n", " fig.add_subplot(1, 3, 1, ylabel=\"Result\")\n", - " plt.imshow(result[0, :, :, slice_nb], cmap='gray')\n", + " plt.imshow(result[0, :, :, slice_nb].T, cmap='gray')\n", "\n", " fig.add_subplot(1, 3, 2)\n", - " plt.imshow(result[0, :, slice_nb, :], cmap='gray')\n", + " plt.imshow(result[0, :, slice_nb, :].T, cmap='gray')\n", "\n", " fig.add_subplot(1, 3, 3)\n", - " plt.imshow(result[0, slice_nb, :, :], cmap='gray')\n", + " plt.imshow(result[0, slice_nb, :, :].T, cmap='gray')\n", "\n", " plt.show()" ] @@ -173,16 +179,6 @@ "### Initialization" ] }, - { - "cell_type": "markdown", - "id": "63ee7477", - "metadata": {}, - "source": [ - "Before you start running the notebook, make sure you download the CT-image from [here](https://github.com/theibsi/data_sets/tree/master/ibsi_1_ct_radiomics_phantom/dicom) and organize your folder as shown in the figure below:\n", - "\n", - "\n" - ] - }, { "cell_type": "markdown", "id": "c399fcd4", @@ -195,15 +191,13 @@ "cell_type": "code", "execution_count": 4, "id": "e615b158", - "metadata": { - "scrolled": true - }, + "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-13 22:35:52,356\tINFO worker.py:1743 -- Started a local Ray instance. View the dashboard at \u001b[1m\u001b[32m127.0.0.1:8265 \u001b[39m\u001b[22m\n" + "2026-02-04 11:31:31,071\tINFO worker.py:2003 -- Started a local Ray instance. View the dashboard at \u001b[1m\u001b[32m127.0.0.1:8266 \u001b[39m\u001b[22m\n" ] }, { @@ -219,7 +213,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████| 61/61 [00:00<00:00, 1275.56it/s]\n" + "100%|█████████████████████████████████████████████████████████████████████████████████| 61/61 [00:00<00:00, 371.96it/s]\n" ] }, { @@ -234,7 +228,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 26715.31it/s]\n", + "100%|██████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 1003.42it/s]\n", ":job_id:01000000\n", ":task_name:process_files_wrapper\n" ] @@ -253,8 +247,8 @@ "name": "stderr", "output_type": "stream", "text": [ - "WARNING:root:The patient ID of the following file: 1__CT.CTscan.npy does not respect the MEDimage naming convention 'study-institution-id' (Ex: Glioma-TCGA-001)\n", - "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 5121.25it/s]" + "WARNING:root:The patient ID of the following file: 1__CT.CTscan.npy does not respect the MEDiml naming convention 'study-institution-id' (Ex: Glioma-TCGA-001)\n", + "100%|██████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 1001.98it/s]\n" ] }, { @@ -263,19 +257,12 @@ "text": [ "DONE\n" ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n" - ] } ], "source": [ "# Intialize the DataManager class\n", "path_to_dicoms = Path(os.getcwd()) / \"data\" / \"CTimage\"\n", - "dm = MEDimage.wrangling.DataManager(path_to_dicoms=path_to_dicoms, path_save=path_to_dicoms)\n", + "dm = MEDiml.wrangling.DataManager(path_to_dicoms=path_to_dicoms, path_save=path_to_dicoms)\n", "\n", "# Process the DICOM scan\n", "dm.process_all_dicoms()\n", @@ -343,7 +330,7 @@ "metadata": {}, "outputs": [], "source": [ - "vol_obj_init, roi_obj_init = MEDimage.processing.segmentation.get_roi_from_indexes(MEDinstance,\n", + "vol_obj_init, roi_obj_init = MEDiml.processing.segmentation.get_roi_from_indexes(MEDinstance,\n", " name_roi='{GTV-1}',\n", " box_string='full')" ] @@ -366,7 +353,7 @@ "path_settings = Path(os.getcwd()) / \"settings\" # Path to the script settings/configuration folder\n", "\n", "# Load script parameters\n", - "im_params = MEDimage.utils.json_utils.load_json(path_settings / f'IBSI2Phase2B_settings.json')\n", + "im_params = MEDiml.utils.json_utils.load_json(path_settings / f'IBSI2Phase2B_settings.json')\n", "\n", "filter_name = ''\n", "\n", @@ -433,7 +420,7 @@ "outputs": [], "source": [ "# Extract initial diagnostic featues\n", - "diag_init = MEDimage.biomarkers.diagnostics.extract_all(vol_obj_init, roi_obj_init, roi_obj_init, 'initial')" + "diag_init = MEDiml.biomarkers.diagnostics.extract_all(vol_obj_init, roi_obj_init, roi_obj_init, 'initial')" ] }, { @@ -455,7 +442,7 @@ "roi_obj_morph = deepcopy(roi_obj_init)\n", "\n", "# Intensity Mask\n", - "vol_obj = MEDimage.processing.interpolation.interp_volume(\n", + "vol_obj = MEDiml.processing.interpolation.interp_volume(\n", " medscan=MEDinstance,\n", " vol_obj_s=vol_obj_init,\n", " image_type='image',\n", @@ -463,7 +450,7 @@ " box_string='full'\n", ")\n", "# Morphological Mask\n", - "roi_obj_morph = MEDimage.processing.interpolation.interp_volume(\n", + "roi_obj_morph = MEDiml.processing.interpolation.interp_volume(\n", " medscan=MEDinstance,\n", " vol_obj_s=roi_obj_init,\n", " image_type='roi', \n", @@ -529,7 +516,7 @@ "roi_obj_int = deepcopy(roi_obj_morph)\n", "\n", "# outlier re-segmentation\n", - "roi_obj_int.data = MEDimage.processing.resegmentation.range_re_seg(\n", + "roi_obj_int.data = MEDiml.processing.resegmentation.range_re_seg(\n", " vol=vol_obj.data, \n", " roi=roi_obj_int.data,\n", " im_range=MEDinstance.params.process.im_range\n", @@ -552,7 +539,7 @@ "outputs": [], "source": [ "# Post-resegmentation diagnostic features extraction:\n", - "diag_re_seg = MEDimage.biomarkers.diagnostics.extract_all(vol_obj, roi_obj_int, roi_obj_morph, 'reSeg')" + "diag_re_seg = MEDiml.biomarkers.diagnostics.extract_all(vol_obj, roi_obj_int, roi_obj_morph, 'reSeg')" ] }, { @@ -580,7 +567,7 @@ "id": "d9a1d18c", "metadata": {}, "source": [ - "Unlike the phase 1, we will use the *MEDimage* sub-module *filter* method ``apply_filter`` to filter the CT image. The method uses the same steps as in phase 1. \n", + "Unlike the phase 1, we will use the *MEDiml* sub-module *filter* method ``apply_filter`` to filter the CT image. The method uses the same steps as in phase 1. \n", "\n", "The parameters needed are already in the ``MEDscan`` class instance." ] @@ -592,7 +579,7 @@ "metadata": {}, "outputs": [], "source": [ - "vol_obj = MEDimage.filters.apply_filter(MEDinstance, vol_obj)" + "vol_obj = MEDiml.filters.apply_filter(MEDinstance, vol_obj)" ] }, { @@ -610,7 +597,7 @@ "metadata": {}, "outputs": [], "source": [ - "vol_int_re = MEDimage.processing.roi_extract(\n", + "vol_int_re = MEDiml.processing.roi_extract(\n", " vol=vol_obj.data, \n", " roi=roi_obj_int.data\n", " )" @@ -660,7 +647,7 @@ "metadata": {}, "outputs": [], "source": [ - "int_hist = MEDimage.biomarkers.intensity_histogram.extract_all(vol=vol_int_re)" + "int_hist = MEDiml.biomarkers.intensity_histogram.extract_all(vol=vol_int_re)" ] }, { @@ -678,7 +665,7 @@ "metadata": {}, "outputs": [], "source": [ - "stats = MEDimage.biomarkers.stats.extract_all(vol=vol_int_re, intensity_type=\"definite\")" + "stats = MEDiml.biomarkers.stats.extract_all(vol=vol_int_re, intensity_type=\"definite\")" ] }, { @@ -732,10 +719,10 @@ " \"diag_min_int_interp_reseg\": -997.0\n", " },\n", " \"int_hist_3D\": {\n", - " \"Fih_mean\": 0.015125684037540313,\n", - " \"Fih_var\": 0.9960209873915681,\n", - " \"Fih_skew\": 72.8851703833975,\n", - " \"Fih_kurt\": 5726.241529761043,\n", + " \"Fih_mean\": 0.015125684037540315,\n", + " \"Fih_var\": 0.996020987391568,\n", + " \"Fih_skew\": 72.88517038339751,\n", + " \"Fih_kurt\": 5726.241529761044,\n", " \"Fih_median\": 37.33600000000005,\n", " \"Fih_min\": -906.1759999999999,\n", " \"Fih_P10\": -389.3151999999997,\n", @@ -809,7 +796,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -834,9 +821,9 @@ ], "metadata": { "kernelspec": { - "display_name": "medimage", + "display_name": "mediml", "language": "python", - "name": "medimage" + "name": "mediml" }, "language_info": { "codemirror_mode": { @@ -848,7 +835,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.13" + "version": "3.9.18" } }, "nbformat": 4, diff --git a/notebooks/tutorial/BatchExtractor-Tutorial.ipynb b/notebooks/tutorial/BatchExtractor-Tutorial.ipynb index a95763e..5b0cee3 100644 --- a/notebooks/tutorial/BatchExtractor-Tutorial.ipynb +++ b/notebooks/tutorial/BatchExtractor-Tutorial.ipynb @@ -30,7 +30,7 @@ "source": [ "## Introduction\n", "\n", - "Running this notebook requires running the [DataManager-tutorial notebook](https://colab.research.google.com/github/MahdiAll99/MEDimage/blob/dev/notebooks/tutorial/DataManager-Tutorial.ipynb). We also recommend that you take a look at [MEDscan-Tutorial notebook](https://colab.research.google.com/github/MahdiAll99/MEDimage/blob/dev/notebooks/tutorial/MEDscan-Tutorial.ipynb) as well.\n", + "Running this notebook requires running the [DataManager-tutorial notebook](https://colab.research.google.com/github/MEDomicsLab/MEDiml/blob/dev/notebooks/tutorial/DataManager-Tutorial.ipynb). We also recommend that you take a look at [MEDscan-Tutorial notebook](https://colab.research.google.com/github/MEDomicsLab/MEDiml/blob/dev/notebooks/tutorial/MEDscan-Tutorial.ipynb) as well.\n", "\n", "This notebook is a tutorial of radiomics batch extraction using the *MEDimage* package and specifically the ``BatchExtractor`` class. For this task, the ``BatchExtractor`` class is the main object used to order scans and prepare batches and run processing and features extraction. The class extracts all type of family features and organizes the results in json files and csv tables.\n", "\n", diff --git a/notebooks/tutorial/DataManager-Tutorial.ipynb b/notebooks/tutorial/DataManager-Tutorial.ipynb index 9f6ffb7..817e0fc 100644 --- a/notebooks/tutorial/DataManager-Tutorial.ipynb +++ b/notebooks/tutorial/DataManager-Tutorial.ipynb @@ -1362,7 +1362,7 @@ "id": "630541c6", "metadata": {}, "source": [ - "Now that you understand how the ``DataManager`` class work, we recommend you follow the [MEDscan tutorial](https://colab.research.google.com/github/MahdiAll99/MEDimage/blob/dev/notebooks/tutorial/MEDscan-Tutorial.ipynb) for more details on the ``MEDscan`` class." + "Now that you understand how the ``DataManager`` class work, we recommend you follow the [MEDscan tutorial](https://colab.research.google.com/github/MEDomicsLab/MEDiml/blob/dev/notebooks/tutorial/MEDscan-Tutorial.ipynb) for more details on the ``MEDscan`` class." ] } ], diff --git a/notebooks/tutorial/MEDscan-Tutorial.ipynb b/notebooks/tutorial/MEDscan-Tutorial.ipynb index 9e902d9..8210ebe 100644 --- a/notebooks/tutorial/MEDscan-Tutorial.ipynb +++ b/notebooks/tutorial/MEDscan-Tutorial.ipynb @@ -43,7 +43,7 @@ "source": [ "## Introduction\n", "\n", - "We recommed you run the [DataManager-Tutorial](https://colab.research.google.com/github/MahdiAll99/MEDimage/blob/dev/notebooks/tutorial/DataManager-Tutorial.ipynb) before going through this one.\n", + "We recommed you run the [DataManager-Tutorial](https://colab.research.google.com/github/MEDomicsLab/MEDiml/blob/dev/notebooks/tutorial/DataManager-Tutorial.ipynb) before going through this one.\n", "\n", "This notebook is a tutorial for the ``MEDscan`` class to give a detailed introduction & explanation on how the Python class is created, used and saved. The ``MEDscan`` class is the main object used in the *MEDimage* package either when it comes to processing, features extraction or any other type of other image analysis. It contains many attributes, child classes and many methods that holds information about the imaging data we're using, the processing and computation parameters etc. This makes the *MEDimage* package an excellent tool for radiomics studies and the ``MEDscan`` class a main tool to the use of this package. \n", "\n", diff --git a/pyproject.toml b/pyproject.toml index 407c2a0..a889645 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "mediml" -version = "0.9.9" +version = "0.9.10" description = "MEDiml is a Python package for processing and extracting features from medical images" authors = ["MEDomics Consortium "] license = "GPL-3.0" diff --git a/setup.py b/setup.py index d553eff..110a76a 100644 --- a/setup.py +++ b/setup.py @@ -14,7 +14,7 @@ setup( name="MEDiml", - version="0.9.9", + version="0.9.10", author="MEDomics consortium", author_email="medomics.info@gmail.com", description="Python Open-source package for medical images processing and radiomic features extraction",