MIC-DKFZ/MedNeXt
[MICCAI 2023] MedNeXt is a fully ConvNeXt architecture for 3D medical image segmentation.
This project helps medical researchers and clinicians automatically identify and outline specific structures or abnormalities within 3D medical images, such as MRI or CT scans. You input raw 3D medical image data, and it outputs segmented images highlighting regions of interest. It's designed for medical imaging specialists, radiologists, and researchers working with volumetric scans.
487 stars. No commits in the last 6 months.
Use this if you need a specialized tool for segmenting anatomical structures or lesions in 3D medical scans, particularly when dealing with datasets that have limited annotations.
Not ideal if you are working with 2D medical images or general-purpose image segmentation tasks outside of the medical domain.
Stars
487
Forks
58
Language
Python
License
Apache-2.0
Last pushed
Nov 02, 2024
Commits (30d)
0
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