Automatic segmentation of female urine control anatomical elements and related structures in MRI images based on deep learning
Objective To construct an automatic segmentation model to segment female urine control anatomy on MRI images based on deep learning methods in order to improve the segmentation efficiency and accuracy. Methods A dataset comprising 49 female pelvic floor muscle MRI images [30 women with varying d...
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| Main Authors: | ZHANG Ziqin, WU Yi, ZHANG Xiaoqin |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Journal of Army Medical University
2025-07-01
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| Series: | 陆军军医大学学报 |
| Subjects: | |
| Online Access: | https://aammt.tmmu.edu.cn/html/202406055.html |
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