xmindflow/MSA-2Net

[BMVC 2024] Official repository of the paper titled "MSA^2 Net: Multi-scale Adaptive Attention-guided Network for Medical Image Segmentation"

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This project helps medical professionals, researchers, and AI developers precisely outline organs, tumors, or other structures within medical images like X-rays, MRIs, or CT scans. It takes raw medical images as input and produces segmented images with clear delineations of specific anatomical or pathological regions. The primary users are those who analyze medical scans for diagnosis, treatment planning, or scientific study.

No commits in the last 6 months.

Use this if you need to accurately segment various tissues and structures in medical images, especially when dealing with significant variations in size, shape, and density of features.

Not ideal if you are looking for a general-purpose image segmentation tool outside of medical imaging, or if you do not have access to a GPU with at least 12GB of memory.

medical-imaging radiology dermatology biomedical-research anatomical-segmentation
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 9 / 25
Maturity 16 / 25
Community 8 / 25

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Stars

70

Forks

4

Language

Python

License

MIT

Last pushed

Oct 02, 2025

Commits (30d)

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