Post-surgical Endometriosis Segmentation in Laparoscopic Videos
Fuente:
arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Acceso en línea: | |
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| _version_ | 1866911213625016320 |
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| author | Leibetseder, Andreas Schoeffmann, Klaus Keckstein, Jörg Keckstein, Simon |
| author_facet | Leibetseder, Andreas Schoeffmann, Klaus Keckstein, Jörg Keckstein, Simon |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_13899 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Post-surgical Endometriosis Segmentation in Laparoscopic Videos Leibetseder, Andreas Schoeffmann, Klaus Keckstein, Jörg Keckstein, Simon Computer Vision and Pattern Recognition Machine Learning Multimedia 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. |
| title | Post-surgical Endometriosis Segmentation in Laparoscopic Videos |
| topic | Computer Vision and Pattern Recognition Machine Learning Multimedia |
| url | https://arxiv.org/abs/2510.13899 |