1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.CV2026
GUMP-Net: An interpretable model-data-driven intelligent algorithm for multi-class pelvic segmentation
Liheng Wang, Yinghui Zhang, Licheng Zhang +3
Pelvic segmentation is one of the most important and fundamental research problems in precise and intelligent diagnosis and treatment, as well as surgical planning and navigation f…
eess.IV2025★ 1 cited
Benchmark of Segmentation Techniques for Pelvic Fracture in CT and X-ray: Summary of the PENGWIN 2024 Challenge
Yudi Sang, Yanzhen Liu, Sutuke Yibulayimu +33
The segmentation of pelvic fracture fragments in CT and X-ray images is crucial for trauma diagnosis, surgical planning, and intraoperative guidance. However, accurately and effici…