mlsanityData to 14 Oct 2026

Post-surgical Endometriosis Segmentation in Laparoscopic Videos

arXiv 2510.13899 ↗First posted 14 Oct 2025cs.CV cs.LG cs.MMcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 6 of its 8 references that are in the map. First posted on arXiv 14 Oct 2025.

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6 of 8 references.

References · 6

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2014Microsoft COCO: Common Objects in Contextcited by 17,608
  3. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,639
  4. 2017Mask R-CNNcited by 7,277
  5. 2015Fast R-CNNcited by 2,933
  6. 2025GLENDA: Gynecologic Laparoscopy Endometriosis Datasetcited by 2

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