HealthX-Lab/DiffusionSynCTSeg
[MICCAI2024] Official implementation of "CT-Based Brain Ventricle Segmentation via Diffusion Schrödinger Bridge without target domain ground truths"
This project offers an automated way to identify and outline brain ventricles from CT scans, which is crucial for emergency neurosurgeries. It takes unpaired CT and MRI images (where only MRI images have known ventricle outlines) as input and produces CT scans with accurate ventricle segmentations, along with a confidence measure for the result. Neurosurgeons, radiologists, and clinicians involved in brain injury or stroke management would use this tool.
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Use this if you need a reliable method to quickly and accurately segment brain ventricles from CT scans, especially when annotated CT data is scarce.
Not ideal if you require segmentation of other brain structures besides ventricles or if you primarily work with MRI scans that already have detailed annotations.
Stars
10
Forks
2
Language
Python
License
Apache-2.0
Category
Last pushed
Nov 14, 2024
Commits (30d)
0
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