Segmentation of Ovarian Cancer using Active Contour and Random Walker Algorithm
P J Ruchitha, Y Sai Richitha, Ashwini Kodipalli, Roshan Joy Martis
Abstract
Image Processing nowadays has been commonly used in different medical fields and includes many types of techniques such as storage, communication, presentation, extraction, detection, image gaining, and surgical planning which helps in improving early detection and treatment stage. Early detection is easier in the treatment especially in the case of ovarian cancer. Ovarian cancer has become one among the frequently occuring diseases in 1 in every 8 women these days, this increase in the number of women getting this cancer has drawn the attention of many medical communities. Statistics indicate that ovarian cancer is one of the 10 usual cancers in women. It is the deadliest gynecologic cancer and takes many lives. Early identification of this cancer is very much important for an efficacious diagnosis. There have been many algorithms used to detect ovarian cancer. Here are two algorithms active contour and random walker that are used to detect ovarian cancer and to find the better approach out of them.