Endometriosis Annotation in Endoscopic Videos

Andreas Leibetseder, Bernd Münzer, Klaus Schoeffmann, J. Keckstein
In: 2017 IEEE International Symposium on Multimedia (ISM) · 2017 · pp. 364–365 · doi:10.1109/ism.2017.69 · W2782169241
article OA: closed CC0 ⤵ 2 in-corpus citations
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⚙ AI-generated summary by claude@2026-07, 2026-07-19 ⓘ

This paper presents a tool for annotating endoscopic video frames to help identify endometriosis, aiming to optimize the time-consuming post-surgery video analysis required of physicians.

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Abstract

When regarding physicians' tremendously packed timetables, it comes as no surprise that they start managing even critical situations hastily in order to cope with the high demands laid out for them. Apart from treating patients' conditions they as well are required to perform time-consuming administrative tasks, including post-surgery video analyses. Concerning documentation of minimally invasive surgeries (MIS), specifically endoscopy, such processes usually involve repeatedly perusing through lengthy, in the worst case uncut recordings - a redundant task that nowadays can be optimized by using readily available technology: we present a tool for annotating endoscopic video frames targeting a specific use case - endometriosis, i.e. the dislocation of uterine-like tissue.

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Condition tags

endometriosis

Citation neighborhood

Papers in the corpus that this work cites (lower rings, blue) and that cite this one (upper rings, green). Dot size scales with the paper's in-corpus citation count — bigger dot = more influential within the endo/adeno field. Click a dot to open that paper. [ expand to 2 hops ] — adds papers reached through this work's immediate citers/citees. Heavier; up to 60 extra dots.

References (16)

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last seen: 2026-06-10T17:14:06.276822+00:00
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