Sahrim, MMSahrimAziz, ANAANAAzizWan Zakiah Wan IsmailIsmail I.Jamaludin J.Balakrishnan, SRSRBalakrishnan2024-05-292024-05-292018Wan Ismail, W. Z. (2018). Automatic feature description of Endometrioma in Ultrasonic images of the ovary. International Journal of Integrated Engineering, 10(1). Retrieved from https://publisher.uthm.edu.my/ojs/index.php/ijie/article/view/25072229-838XWOS:000436854600029https://publisher.uthm.edu.my/ojs/index.php/ijie/article/view/2507https://oarep.usim.edu.my/handle/123456789/11414Endometriosis 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 studieden-USEndometrioma cystsultra-sonographicpattern recognitionimage processing techniqueultrasound scanArticle186188101