🧠 Medical Organ Classifier 🫁

The Medical Organ Classifier is a cutting-edge, AI-powered application designed to classify medical organ images with precision and ease. Leveraging advanced deep learning models 🧑‍💻, this tool delivers accurate predictions with confidence scores—all through an intuitive graphical interface 🎨. Built with TensorFlow/Keras, it offers flexibility for customization and expansion 🚀.

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🌟 Key Features

🖥️ Interactive GUI

• 🔍 Load and utilize pre-trained TensorFlow/Keras models.
• 📂 Upload medical images and receive predictions with detailed confidence scores.
• 🖱️ User-friendly interface for seamless interaction.

🩺 Dynamic Classification

• 🧠 Supports classification of multiple organs, including:
  • Brain
  • Hand
  • Liver
  • Lung
• 📊 Delivers results with confidence levels to ensure reliability.

⚙️ Customizable and Scalable

• ➕ Easily extend functionality by adding new organ classes.
• 🛠️ Simply update the model and its corresponding JSON label file to support additional categories.

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📸 Model Demonstration

🔬 Example Trials:

🩻 Liver Image Classification:

🫁 Lung Image Classification:

🖐️ Hand X-Ray Image Classification:

✋ Normal Hand Image Classification:

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🧠 Deep Learning Model

Model Overview

• 🤖 Powered by a TensorFlow/Keras pre-trained model.
• 📜 Outputs classes based on a JSON label file (e.g., organ_model.json).
• Example JSON format for classification labels:

  ["Brain", "Hand", "Liver", "Lung"]  

🏋️ Training a New Model

1. 📘 Open the Training_notebook.ipynb in the training/ directory.
2. 📂 Prepare your dataset and follow the steps outlined in the notebook.
3. 💾 Save the trained model as organ_model.h5.
4. 📝 Update the organ_model.json file to match the output classes of the new model.

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⚙️ Installation Guide

Prerequisites

• 🐍 Python: Version 3.8 or higher.
• 🖥️ Git: To clone the repository.

Steps to Install

1. Clone the Repository

   git clone https://github.com/yourusername/MedicalOrganClassifier.git  
   cd MedicalOrganClassifier  

2. Install Dependencies

   pip install -r requirements.txt  

3. Place the Model Files

   • 🗂️ Add the pre-trained model file (e.g., organ_model.h5) to the models/ directory.
   • 📝 Ensure the organ_model.json file matches the class labels for the model and is placed in the app/ directory.

4. Run the Application

   python app/main.py  

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📌 Important Notes

File Compatibility

• 📂 The model file (e.g., organ_model.h5) and label file (organ_model.json) must correspond.
• ✅ Ensure the number of classes in the model matches the labels in the JSON file.

🛠️ Common Issues

• ❌ Error During Prediction: Ensure the model and JSON file are compatible.
• 🔍 Verification: Use the "Load Model" feature in the app to confirm compatibility.

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🤝 Contributing

We ❤️ contributions to enhance this project! To contribute:

1. Fork the repository.
2. Create a feature branch.
3. Submit a pull request with detailed information about your changes.

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📜 License

This project is licensed under the MIT License. Refer to the LICENSE file for more details.

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👥 Meet the Team

This project was developed collaboratively by a dedicated team:

• Sief Eldin Sameh
• Fahd Ahmed
• Ahmed Salem
• Karim Farid

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Thank you for using the Medical Organ Classifier! 🎉