Detection and Classification Using Multi-Layer Perceptrons

Setup

1. Create a virtual environment and activate it:

   python3 -m venv venv
   source venv/bin/activate

2. Install dependencies:

   pip install -r requirements.txt

Dataset

Brain Tumor (MRI)

• Download the dataset from Kaggle: Brain Tumor MRI Dataset.
• Extract the Train and Test folders to the Data/Brain_Tumor folder in the main project directory.

Fetus (Ultrasound)

• Download the dataset from Kaggle: Ultrasound Fetus Dataset.
• Extract the train and test folders to the Data/Fetus folder in the main project directory.

Liver (Ultrasound)

• Download the dataset from Kaggle: Annotated Ultrasound Liver images Dataset.
• Extract the 727660 folder to main project directory and run python liver_test_train_data.py.
• Delete the 727660 folder in the main project directory.

Directory

After the setup is completed, the file directory should look like this:

├── Data
│   ├── Brain_Tumor
│   │   ├── Train
│   │   └── Test
│   ├── Fetus
│   │   ├── train
│   │   └── test
|   └── Liver
│       ├── train
│       └── test
├── Models
│   ├── brain_tumor_model.h5
│   ├── fetus_model.h5
│   └── liver_model.h5
├── venv/
├── brain_tumor_mlp_model_detection.ipynb
├── fetus_mlp_model_detection.ipynb
├── liver_mlp_model_detection.ipynb
├── liver_test_train_data.py
├── requirements.txt
├── venv/
└── README.md