A Survey On Various Segmentation Methods In Medical Images

Jackulin DuraiRani, A., Yamini, C., Sivaranjani, B. and Pushpa Priya, A.

This paper makes a review on various segmentation methods for automatic extraction of images from CT and MR images in medical field. Precise segmentation of medical images is a key step in contouring during radiotherapy planning. Computed topography (CT) and Magnetic resonance (MR) imaging systems are the most widely used radiographic techniques in identification, clinical trails and for treatment procedure. For the past years, many image segmentation techniques have been proposed by various researchers. These segmentation techniques can be classified into three types, (1) characteristic feature threshold or clustering, (2) edge detection, and (3) region extraction. This survey paper encounters some of these techniques. In biomedical image segmentation, most commonly used techniques fall into the categories of characteristic feature threshold or clustering and edge detection. This paper gives details of automatic segmentation methods, specifically for CT and MR images. The aim is to discuss the problems meet in segmentation of CT and MR images, and the relative advantages and disadvantages of those methods currently available for segmentation of medical images.

Download PDF: