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This Github repository contains a comprehensive implementation of a deep learning model for detecting and segmenting tumors in medical images. The model is designed to process MRI and CT scans and uses state-of-the-art techniques to accurately identify tumor regions.

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Anamaya1729/Detecting-and-Segmenting-Tumor

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Tumor Detection and Segmentation

This Github repository contains a comprehensive implementation of a deep learning model for detecting and segmenting tumors in medical images. The model is designed to process MRI and CT scans and uses state-of-the-art techniques to accurately identify tumor regions.

Getting Started

To get started, clone the repository to your local machine:

https://github.com/Anamaya1729/Detecting-and-Segmenting-Tumor/

Prerequisites

  • Python 3
  • TensorFlow 2
  • Keras
  • Numpy
  • OpenCV

Architecture

The model is based on a U-Net architecture and is trained on a large dataset of annotated medical images. The implementation is highly modular, allowing for easy customization and experimentation with different hyperparameters and network architectures.

Contributing

Contributions are always welcome! Please feel free to open an issue or submit a pull request with any changes or improvements.

About

This Github repository contains a comprehensive implementation of a deep learning model for detecting and segmenting tumors in medical images. The model is designed to process MRI and CT scans and uses state-of-the-art techniques to accurately identify tumor regions.

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