自动识别腹腔镜视频中深色子宫内膜异位病灶并标注
Post-surgical Endometriosis Segmentation in Laparoscopic Videos
- 基于深度学习分析腹腔镜手术视频，定位深色病灶
- 生成多色覆盖图与检测摘要，提升视频浏览效率
- 专为妇科医生优化，辅助非专科医师快速识别
子宫内膜异位症是一种常见女性疾病，在体内不同位置呈现多种视觉形态，导致识别困难且易出错，尤其对非专业医疗人员。为协助妇科医生诊疗，本文介绍一种演示系统，专门训练用于分割最常见的一种视觉表现——深色子宫内膜植入物。该系统可分析腹腔镜手术视频，对识别出的病灶区域进行多色标记，并生成检测摘要，以改善视频浏览体验。
原文摘要 · Abstract (English)
Endometriosis is a common women's condition exhibiting a manifold visual appearance in various body-internal locations. Having such properties makes its identification very difficult and error-prone, at least for laymen and non-specialized medical practitioners. In an attempt to provide assistance to gynecologic physicians treating endometriosis, this demo paper describes a system that is trained to segment one frequently occurring visual appearance of endometriosis, namely dark endometrial implants. The system is capable of analyzing laparoscopic surgery videos, annotating identified implant regions with multi-colored overlays and displaying a detection summary for improved video browsing.
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