Journal of Computer Science

Study of Segmentation Technique and Stereology to Detect PCO Follicles on USG Images

Untari Novia Wisesty, Irba Fairuz Thufailah, Ria May Dewi, Adiwijaya and Jondri

DOI : 10.3844/jcssp.2018.351.359

Journal of Computer Science

Volume 14, Issue 3

Pages 351-359

Abstract

Polycystic Ovary Syndrome is a hormonal health problem in women who are in the reproductive period. One feature of this syndrome is that there are 12 or more follicles in the ovary with a diameter of 2-9 mm. This syndrome can cause menstrual cycles problems and even a problem in conceiving a child. Currently, follicle detection is still done manually by Obstetricians and it takes a long time to get accurate result. Therefore, a system that can detect follicles and calculate its size automatically is required. This paper uses Global Basic Threshold and Otsu Threshold method to get the form of follicles in the process of image binarization and follicle segmentation and stereology approach to calculate the number and diameter of the follicle. The result of system testing shows that the system with Global Basic Threshold method and stereology had a sensitivity rate of 86%, a specificity of 15 and a 33% detection size error rate. While using the method Otsu Threshold and stereology showed sensitivity results of 89%, specificity 14 and 35% detection size error rate.

Copyright

© 2018 Untari Novia Wisesty, Irba Fairuz Thufailah, Ria May Dewi, Adiwijaya and Jondri . This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.