/ml-services-in-healthcare

Development of a companion application to help medical staff in more efficient segmentation of brain tumors and its sub-regions from mri images, including patient survival prediction.

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ml-services-in-healthcare

Development of a companion application to help medical staff in more efficient segmentation of brain tumors and its sub-regions from mri images, including patient survival prediction. MRI Brain Tumor Segmentation U-Net approach Problem definiton Segmentation of tumors in pre-operative MRI scans.

Each pixel on image must be labeled:

  • Pixel is part of a tumor area (1 or 2 or 3) can be one of multiple classes or subregions
  • Anything else > pixel is not on a tumor region (0)

The subregions of tumor considered for evaluation are:

  • The "enhancing tumor" (ET).
  • The "tumor core" (TC).
  • The "whole tumor" (WT). The provided segmentation labels have values of 1 for CORE, 2 for EDEMA, 4 for ENHANCING TUMOR, and 0 for everything else.