A Review of Image Segmentation Techniques Applied to Medical Images

Medical images have made a great impact on diagnosis, clinical studies and treatment planning. The most important part of medicalimage processing is segmentation. It is one of the hardest and most frequently required steps in Medical image processing. Many segmentation methods have been proposed for medical images. Methods for performing medical image segmentation vary widely depending on imaging modality, the specific application and type of body part tobe studied. The performance of these techniques is highly associated with the extraction of anatomic structures and separation of suspicious regions from the background and soft tissues effectively.This review paper investigates applicability of different algorithms for computer-aided segmentation of medical images. The study revealed that several algorithms have been explored in the literature for segmentation of anatomic structures from different medical images. Among them k-means, fuzzy c-means and variations of kmeans clustering techniques are extensively used for medical image segmentation.