/kaggle_vol-3D-classify

Predict the status of a genetic biomarker important for brain cancer treatment

Primary LanguageJupyter NotebookMIT LicenseMIT

Kaggle competitions on 3D volumes

CI complete testing Code formatting codecov pre-commit.ci status

The goal is prediction fracture in whole neck 3D scans. The organizers provide 2k cases with partially annotated fractures as bounding boxes or/and pixel-wise segmentations.

Sample brain visual

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_vol-3D-classify/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