Automatic feature description of Endometrioma in Ultrasonic images of the ovary

Mus’ab Sahrim, Ain Nadiah Abdul Aziz, Wan Zakiah Wan Ismail, Irneza Ismail, Juliza Jamaludin, S. Balakrishnan, Sharma Rao Balakrishnan
In: International Journal of Integrated Engineering · 2018 · vol. 10(1) · doi:10.30880/ijie.2018.10.01.028 · W2884415305
article OA: diamond CC0 ⤵ 3 in-corpus citations
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⚙ AI-generated summary by gemini-2.5-flash-lite, 2026-06-08 ⓘ

This study developed a pattern recognition method using image processing techniques to automatically extract features from ultrasonic images for endometrioma description.

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Abstract

Endometriosis cyst or endometrium is commonly found in women with subfertility. Traditionally, medical technologies fail to detect the disease automatically and it is fully dependent on the doctors to determine the peritoneal disease where it may lead to inaccurate findings. A method of assessment may give more accurate detection without the need for surgical procedure, especially in monitoring disease recurrence. This will avoid surgical risk and will not delay the management. In this study, the feature description is developed using pattern recognition, involving image processing techniques; the ultrasonic images is used as input in which the region of interest of images, image segmentation, feature extraction are studied

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endometriosisendometrioma

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last seen: 2026-06-04T00:00:01.174412+00:00
License: CC0 · commercial use OK