https://github.com/cutupdev/brain-tumors-segmentation-using-encoder-decoder

This is repository for segmentation brain tumors from Brain MRI image. It used Convolutional Neural Network(CNN).
https://github.com/cutupdev/brain-tumors-segmentation-using-encoder-decoder

cnn decoder encoder image-processing jupyter-notebook python tensorflow

Last synced: about 2 months ago
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This is repository for segmentation brain tumors from Brain MRI image. It used Convolutional Neural Network(CNN).

• Host: GitHub
• URL: https://github.com/cutupdev/brain-tumors-segmentation-using-encoder-decoder
• Owner: cutupdev
• Created: 2024-02-20T05:43:14.000Z (11 months ago)
• Default Branch: master
• Last Pushed: 2024-03-11T08:43:06.000Z (10 months ago)
• Last Synced: 2024-10-31T23:34:34.600Z (2 months ago)
• Topics: cnn, decoder, encoder, image-processing, jupyter-notebook, python, tensorflow
• Language: Jupyter Notebook
• Homepage:
• Size: 5.06 MB
• Stars: 2
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
#  Brain Tumors Segmentation

Brain tumor segmentation using deep learning is a helpful tool for physicians to rapidly diagnose brain tumors. In this project, an encoder-decoder architecture is utilized to perform brain tumor segmentation. In particular, we investigated several mode reduction techniques to try to limit the number of input modalities needed to achieve good performance. We utilized pre-processed datasets to train and test, and also implemented our own processing pipeline by stripping the skulls from brain images collected by Stanford Health Care (SHC). The developed model was robust to reduction of imaging modes, and shows promise for future investigation in clinical environments.

![architecture](./result/cancer.JPG)