Hybrid Otsu Segmentation And Thresholding Of Medical Images With Separability Factor
The most important part of medical image processing is image segmentation. Image segmentation is a procedure for extracting the region of interest (ROI) through an automatic or semi-automatic process. Many image segmentation methods have been used in medical applications to segment tissues and body organs. Some of the applications consist of border detection in angiograms of coronary, surgical planning, simulation of surgeries, tumor detection and segmentation, brain development study, functional mapping, blood cells automated classification, mass detection in mammograms, image registration, heart segmentation and analysis of cardiac images, etc. The Otsu method is a popular non-parametric method in medical image segmentation. This paper describes a way of medical image segmentation using optimized Otsu method based on thresholding algorithm. In proposed algorithm, the experimental results show that the new optimized method dramatically increases the separability factor in medical image segmentation while ensuring the final image segmentation quality.