Omid-Nejati/BEFUnet
A Hybrid CNN-Transformer Architecture for Precise Medical Image Segmentation
This project helps medical professionals and researchers precisely outline structures in medical images. It takes raw medical scans (like MRI or CT) and outputs segmented images where specific organs or tissues are clearly delineated. Radiologists, medical image analysts, and clinical researchers would use this to automate and improve the accuracy of image analysis.
No commits in the last 6 months.
Use this if you need highly accurate and automated segmentation of anatomical structures or anomalies from medical imaging data.
Not ideal if your primary need is general image classification or object detection in non-medical contexts.
Stars
73
Forks
11
Language
Python
License
MIT
Last pushed
Jun 01, 2024
Commits (30d)
0
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