MediAnalyze Pro

A comprehensive healthcare data and medical image processing application for managing patient health data, analyzing biomedical signals, processing medical images, and creating interactive visualizations.

Overview

MediAnalyze Pro is a desktop application built with PyQt5 that provides healthcare professionals and researchers with tools to:

• Manage and analyze patient health metrics
• Process and analyze biomedical signals (ECG/EEG)
• Process medical images (X-ray, MRI, CT scans)
• Generate comprehensive data visualizations
• Perform statistical analysis and correlation studies

Features

✅ Implemented Features

Phase 1-2: Foundation & Database

• Project structure and setup
• SQLite database with 6 tables (patients, health_metrics, medical_images, biomedical_signals, correlation_results, spectrum_analysis)
• Complete CRUD operations with relationships

Phase 3-4: Data Management

• CSV data loading with auto-delimiter detection
• Data validation (medical value ranges, data types)
• Bulk data import with progress tracking
• Flexible data retrieval with filtering
• Data export to CSV

Phase 5: Signal Processing

• Synthetic ECG/EEG signal generation
• Signal loading from CSV/TXT/DAT files
• Signal preprocessing (normalization, filtering, noise reduction)
• FFT spectrum analysis (magnitude, power spectrum, PSD)

Phase 6: Image Processing

• Medical image loading (PNG, JPEG, BMP, TIFF, DICOM)
• Image processing operations (grayscale, blur, edge detection, thresholding, CLAHE)
• Image metadata extraction and database storage

Phase 7: Visualization

• Time-series plots
• Scatter plots with correlation analysis
• Correlation heatmaps
• FFT spectrum plots
• Image comparison viewer

Phase 8-13: GUI Application

• Data Management Tab: CSV import, patient CRUD operations, data retrieval
• Health Analysis Tab: Data filtering, correlation analysis (Pearson/Spearman), time-series analysis
• Spectrum Analysis Tab: Signal loading, synthetic generation, FFT analysis with multiple visualizations
• Image Processing Tab: Image upload, processing operations, side-by-side comparison
• Data Visualization Tab: Comprehensive visualization interface for all data types

Technology Stack

• Language: Python 3.8+
• GUI: PyQt5
• Database: SQLite (SQLAlchemy ORM)
• Data Processing: NumPy, Pandas, SciPy
• Image Processing: OpenCV, Pillow
• Visualization: Matplotlib, Seaborn

Installation

Prerequisites

• Python 3.8 or higher
• pip package manager
• make (optional, for Makefile commands)

Quick Start (Using Makefile - Recommended)

1. Clone the repository:

   git clone <repository-url>
   cd "MediAnalyze Pro"

2. Run full setup (creates venv and installs dependencies):

   make setup

3. Activate virtual environment:

   source venv/bin/activate  # On macOS/Linux
   # OR
   venv\Scripts\activate  # On Windows

4. Run the application:

   make run

Manual Setup (Alternative)

1. Clone the repository:

   git clone <repository-url>
   cd "MediAnalyze Pro"

2. Create and activate virtual environment:

   python3 -m venv venv
   source venv/bin/activate  # On macOS/Linux
   # OR
   venv\Scripts\activate  # On Windows

3. Install dependencies:

   pip install -r requirements.txt
   # OR
   make install  # (if venv is active)

Running the Application

Using Makefile (Recommended)

# Launch GUI application
make run

# Run all tests
make test

# Run tests with coverage report
make test-cov

# Initialize database
make init-db

# Clean temporary files
make clean

# View all available commands
make help

Manual Commands

# Launch GUI application
python run_gui.py

# Run all tests
pytest

# Run specific test file
pytest tests/test_database.py

# Run with coverage
pytest --cov=src tests/

# Initialize database
python -m src.database.init_db

Project Structure

MediAnalyze Pro/
├── src/
│   ├── database/          # Database models, CRUD operations
│   ├── data_processing/   # Data loading, filtering, correlation
│   ├── signal_processing/ # FFT analysis, signal generation
│   ├── image_processing/  # Image operations, metadata
│   ├── visualization/    # Plotting functions
│   └── gui/               # PyQt5 GUI components
│       └── tabs/          # Feature tabs (5 tabs implemented)
├── data/                  # Data storage (images, signals, processed data)
├── tests/                 # Unit and integration tests
├── datasets/              # Sample datasets
├── run_gui.py             # Application entry point
└── requirements.txt       # Python dependencies

Usage

Data Management

1. Use Data Management tab to import CSV files with health data
2. View, insert, update, or delete patient records
3. Retrieve and filter data from the database

Health Analysis

1. Load health metrics from database
2. Apply filters (Moving Average, Threshold, Outlier Removal)
3. Compute correlations between metrics (Pearson/Spearman)
4. Generate time-series visualizations

Spectrum Analysis

1. Load signal files or generate synthetic ECG/EEG signals
2. Configure FFT parameters (window function, frequency range)
3. View time-domain, frequency-domain, and power spectrum plots

Image Processing

1. Upload medical images (X-ray, MRI, CT)
2. Apply processing operations (blur, edge detection, thresholding, etc.)
3. Compare original vs processed images side-by-side
4. View image metadata

Data Visualization

1. Select visualization type (Time-Series, Scatter, Heatmap, FFT, Image Comparison)
2. Load data from database, CSV, signal files, or images
3. Configure visualization parameters
4. Generate and export visualizations

Testing

Comprehensive unit tests are available for all modules:

• Database operations
• Data processing (loading, filtering, correlation)
• Signal processing
• Image processing
• Visualization
• GUI components

Run tests with: pytest