6卷 第1期
Hangzhou Dianzi University, Hangzhou, Zhejiang, 310018, China
纸质出版：2026-03-30
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Yihan Lang. (2026). Coverage-Driven Soft Labeling for Surgical Video Temporal Segmentation: Application to Radical Prostatectomy. 生物医学大数据, 6(1), 205-210.
Lang Yihan.Coverage-Driven Soft Labeling for Surgical Video Temporal Segmentation: Application to Radical Prostatectomy[J].Biomedical Data Science,2026,06(01):205-210.
Yihan Lang. (2026). Coverage-Driven Soft Labeling for Surgical Video Temporal Segmentation: Application to Radical Prostatectomy. 生物医学大数据, 6(1), 205-210. DOI： 10.47297/wspbdsWSP2752-630545.20260601.
Lang Yihan.Coverage-Driven Soft Labeling for Surgical Video Temporal Segmentation: Application to Radical Prostatectomy[J].Biomedical Data Science,2026,06(01):205-210. DOI： 10.47297/wspbdsWSP2752-630545.20260601.
Radical prostatectomy
the primary curative treatment for prostate cancer
presents significant challenges due to its complex workflow and technical demands. Recent advances in robotic-assisted surgery and deep learning have enabled intelligent surgical assistance systems. This paper proposes a novel temporal segmentation framework combining VideoMAE feature extraction with MS-TCN++ temporal modeling
enhanced by a coverage-driven soft-label strategy for improved frame-wise classification in prostatectomy videos. Our method effectively addresses key challenges including background dominance
boundary ambiguity
and temporal inconsistencies. Experimental validation demonstrates superior performance in both accuracy and robustness
offering promising potential for real-time surgical monitoring and safety assistance.
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