Lesion Extraction of Endometriotic images using Open Computer Vision

S Visalaxi, Dinah Punnoose, T. Sudalai Muthu
In: 2021 International Conference on Artificial Intelligence and Smart Systems (ICAIS) · 2021 · pp. 747–751 · doi:10.1109/icais50930.2021.9395822 · W3153309046
article OA: closed CC0 ⤵ 4 in-corpus citations
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Abstract

The Endometriosis is caused by the endometriotic tissue that streaks the uterus from outside. A total of 6% of women under child bearing age is affected by the endometriosis disorder. The presence of the tissue can be identified though MRI, Transvaginal Ultra Sound Scan (TVUS), Laparoscopic images and pathological slides. Image based applications are processed using Image Pre-processing, Image Segmentation, Image Enhancement and Feature Extraction techniques. The Open Computer Vision (Open CV) is used to extract the features from Laparoscopic Endometriosis Images (LPI). This paper proposed a method to identify the endometriotic tissue by using the LPI images. The proposed method uses several image processing techniques of OpenCV includes Adaptive Threshold, Contour Mask to extract the lesion area from the Laparoscopic images. The designed algorithm has been experimented and the results yielded 53.5 % mean value intensity in identifying the lesion area.

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endometriosis

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License: CC0 · commercial use OK