Kaggle: Brain Tumor Radiogenomic Classification

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The goal of this challenge is to Predict the status of a genetic biomarker important for brain cancer treatment.

Sample brain visual

With interpolation in Z dimension as it happens it is quite sparse:
Sample brain visual

Each independent case has a dedicated folder identified by a five-digit number.
Within each of these “case” folders, there are four sub-folders, each of them corresponding to each of the structural multi-parametric MRI (mpMRI) scans, in DICOM format.
The exact mpMRI scans included are:

  • FLAIR: Fluid Attenuated Inversion Recovery
  • T1w: T1-weighted pre-contrast
  • T1Gd: T1-weighted post-contrast
  • T2: T2-weighted

The labels/targets are MGMT_value:

Label distribution

Experimentation

install this tooling

A simple way how to use this basic functions:

! pip install https://github.com/Borda/kaggle_brain-tumor-3D/archive/refs/heads/main.zip

run notebooks in Kaggle

local notebooks

some results

Training progress with EfficientNet3D with training for 10 epochs > over 96% validation accuracy:

Training process

Read more here: Source link