Follicle Segmentation using K-means Clustering from Ultrasound Image of Ovary

Detection of number, shape and size of follicles in the ovary can play an important role in the diagnosis and monitoring of different diseases like infertility, PCOS (Polycystic Ovarian Syndrome), ovarian cancer, etc. Nowadays the identification of these characteristics of follicles is done manually by radiologists and doctors from the Ultrasound Images of ovaries. Sometimes manual analysis can be tedious and thus may lead to erroneous results. In this paper, a method is proposed for automatic segmentation of follicles from Ultrasound Images using the K-means clustering technique.