2.5D U-Net for Vascular Segmentation (HiP-CT)

Codebase for supervised segmentation of vasculature in 3D HiP-CT volumes using a 2.5D U-Net (stacked slices as colour channels with 2D convolutions).
This repository adapts and refactors the Team-1 solution from the SenNet + HOA Kaggle competition, as described in the paper below.

• 📄 Primary reference: Vasculature segmentation in 3D hierarchical phase-contrast tomography images of human kidneys (bioRxiv, 2024)
  https://www.biorxiv.org/content/10.1101/2024.08.25.609595v1
• 🔗 Upstream source (Team-1): https://github.com/cns-iu/hra-sennet-hoa-kaggle-2024/tree/main/winning-team-solutions/team-1

A tutorial to run the attached code on the UCL CS HPC is included.

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Example Segmentation

Figure 1: Example output from the adapted 2.5D U-Net pipeline for arteries segmentation.

Figure 2: Example output from the adapted 2.5D U-Net pipeline for cortex segmentation.