Diagnostic Tool for PCOS Classification

Abstract

Poly Cystic Ovarian Syndrome (PCOS) is a common disease of the endocrine gland and is otherwise called as Stein-Leventhal syndrome. Generally about 5 women at the reproductive age are affected by this disease. The real cause of the disease is not exactly known, but the onset of the disease is characterized by the excessive secretion of insulin resistance androgen. There are many different methods to diagnose this condition. The most effective method is the pelvic ultrasound, which confirms the presence of multiple small cysts in the periphery of the ovaries. The ultrasound scan image gives us the visualization of the follicles. Actually there are about three types of ovaries in women. They are classified based on the number and the size of the follicles as normal ovary, cystic ovary and polycystic ovary. If the numbers of follicles are 12 or more than 12 and the diameter is more than 2-9 mm, it is being classified as polycystic ovary. In the conventional method, the follicles are counted manually by a medical expert and verified by the second person. Therefore, it is operator biased. Also, there may be a possibility of overlapping of follicles during the ultrasonographic examination process which lead to the wrong diagnosis. This led to the development of automatic detection and counting of follicle in the ovarian ultrasound image. This method makes use of the image processing techniques to pre-process and segment the region of interest. The algorithm works in such a way that it automatically detects and counts the number of follicles based on the size of the follicles in the image. Finally, the ovary is classified as PCOS present/PCOS absent. This PCOS diagnostic tool would save time a physician who has to spend time in manual tracing of follicles.