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DeepActiveNet-MedSeg

DeepActiveNet-MedSeg is an advanced deep learning framework designed for accurate medical image segmentation using active contours.

Features

  • Employs active contour methods for improved segmentation accuracy.
  • Suitable for various medical imaging tasks.
  • Scalable and easy-to-use training, validation, and prediction scripts.

Installation

Clone the repository:

git clone https://github.com/transmutat/DeepActiveNet-MedSeg.git

Install dependencies:

pip install -r requirements.txt

Usage

Train the model:

python main.py

Validate the model:

python main.py --action=test

Make predictions:

python main.py --action=predict

Contributing

Contributions are welcome! Please fork the repository and submit a pull request for consideration.

License

This project is licensed under the MIT License. See the LICENSE file for details.

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Efficient deep learning model leveraging active contours for precise medical image segmentation.

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