PERFORMANCE ANALYSIS OF SELECTED MEDICAL IMAGE SEGMENTATION ALGORITHMS.

Abstract

The ability to understand images is one of the key areas of research where the target is to understand the components of an image and interpret its meaning. The components of images are not easily understood and interpreted for analysis, therefore image segmentation technique is very necessary and should be taken as significant step during image processing and analysis. Repeatable experiments are required for this research field to progress as image segmentation needed for data processing cannot be adequately achieved in a particular technique. Hence performance analysis of various, commonly used techniques are often needed. However, in this work, three classes of image segmentation algorithms: Edge Detection, Clustering and Thresholding method were simulated in MatLab on infected bladder. The experiments were performed three times to confirm the accuracy of the results evaluated with Dice, Jaccard and cosine co-efficient of fitness values.