https://github.com/michael1ding/rsna-miccai-glioblastoma-mri-classification

MGMT promoter methylation classification model built with EfficientNet3D
https://github.com/michael1ding/rsna-miccai-glioblastoma-mri-classification

Last synced: 17 days ago
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MGMT promoter methylation classification model built with EfficientNet3D

• Host: GitHub
• URL: https://github.com/michael1ding/rsna-miccai-glioblastoma-mri-classification
• Owner: michael1ding
• Created: 2021-09-19T04:32:54.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2022-10-05T17:41:58.000Z (over 2 years ago)
• Last Synced: 2024-12-06T20:21:46.746Z (30 days ago)
• Language: Jupyter Notebook
• Size: 906 KB
• Stars: 0
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
   # RSNA-MICCAI-Glioblastoma-MRI-Classification

 

A malignant tumor in the brain is a life-threatening condition. Known as glioblastoma, it's both the most common form of brain cancer in adults and the one with the worst prognosis, with median survival being less than a year. The presence of a specific genetic sequence in the tumor known as MGMT promoter methylation has been shown to be a favorable prognostic factor and a strong predictor of responsiveness to chemotherapy.

 ![MRI Scans](/mri.png).

Currently, genetic analysis of cancer requires surgery to extract a tissue sample. Then it can take several weeks to determine the genetic characterization of the tumor. Depending upon the results and type of initial therapy chosen, a subsequent surgery may be necessary. If an accurate method to predict the genetics of the cancer through imaging (i.e., radiogenomics) alone could be developed, this would potentially minimize the number of surgeries and refine the type of therapy required.

This repository is a summary of my work building model to classify MRI FLAIR and T1WCE scans showing MGMT promoter methylation in patients with existing glioblastoma.