The diagnostic value of MRI segmentation technique for shoulder joint injuries based on deep learning
Lina Dai, Md Gapar Md Johar, Mohammed Hazim Alkawaz · 2024
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Description
Dai, Johar, and Alkawaz test deep learning to outline shoulder scans, in work from twenty twenty-four. Shoulder injuries in swimmers need exact diagnosis. Magnetic resonance images must be split into bones and tissues before injury can be judged well.
Their network fuses features at many scales, built by merging two known designs. Standard overlap and accuracy scores judged the splits on joint bones and the upper arm bone. Fifty-two swimmers with shoulder injuries from a Guangzhou hospital formed the test group. High overlap scores suggest the model can speed scan reading and make measurements more consistent across readers.
Catalog record
| CREATOR | Lina Dai, Md Gapar Md Johar, Mohammed Hazim Alkawaz |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 45 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |