https://github.com/mdaiyub/brain-tumor-grading

I extracted the tumor features according to the data annotation of all four stages of 3D MRI data. And I deployed Graph Neural Networks based on important features such as First Order Statistics, Shape-based (3D), Shape-based (2D), GLCM, GLRLM, GLSZN, NGTDM, and GLDM.
https://github.com/mdaiyub/brain-tumor-grading

biomarker gnn graph-algorithms pyradiomics python

Last synced: about 5 hours ago
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I extracted the tumor features according to the data annotation of all four stages of 3D MRI data. And I deployed Graph Neural Networks based on important features such as First Order Statistics, Shape-based (3D), Shape-based (2D), GLCM, GLRLM, GLSZN, NGTDM, and GLDM.

• Host: GitHub
• URL: https://github.com/mdaiyub/brain-tumor-grading
• Owner: mdaiyub
• Created: 2023-09-06T17:33:49.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2024-02-08T12:33:39.000Z (9 months ago)
• Last Synced: 2024-02-09T04:24:51.944Z (9 months ago)
• Topics: biomarker, gnn, graph-algorithms, pyradiomics, python
• Language: Jupyter Notebook
• Homepage:
• Size: 3.74 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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# Glioma Tumor Grading

I extracted the tumor features according to the data annotation of all four stages of 3D MRI data. And I deployed Graph Neural Networks based on important features such as First Order Statistics, Shape-based (3D), Shape-based (2D), GLCM, GLRLM, GLSZN, NGTDM, and GLDM. Afterward, a graph neural network to differentiate the grade of glioma tumor.