Special Issue Article Open Access

IMPLEMENTATION & COMPARISON OF DIFFERENT SEGMENTATION ALGORITHMS FOR MEDICAL IMAGING

Abstract

ABSTRACT--- Medical image segmentation refers to the segmentation of known anatomic structures from medical images. Structures include organs or parts such as cardiac ventricles or kidneys, abnormalities such as tumours and cysts, as well as other structures such as vessels, brain structures etc. The complete objective of this segmentation is referred to as computer-aided diagnosis that are used for assisting doctors in evaluating medical imagery or in recognizing abnormal findings in a medical image. Segmentation is done using clustering, region growing, otsu method which separates the cell core structure from background and here input image is a myocardial images obtained with biopsies of a Transplanted heart patient. The above three methods to diagnose the similarity of cell core or tissue of a transplanted heart patient and they identify clearly cell core, fibrous tissue, muscles and tissue rejection in myocardial images of biopsies from heart transplant patients. In this paper, we compared the above three methods using the nonlinear objective assessments like energy and entropy and concluded the best among them is OTSU method.

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