A Review on Recent Research and Implementation Methodologies on Medical Image Segmentation

Abstract

Problem statement: Image segmentation plays a very important role in digital imaging applications for classifying the anatomical structures and other Regions of Interest. Segmentation refers to the process of identifying and isolating the surface and regions of the digital image which corresponds to the structural units. Approach: In the past few decades, many methods have been proposed to segment the digital image. Most of them were based on two basic properties of the pixels in relation to their local neighborhood: discontinuity and similarity. The approaches based on discontinuity partition of an image are performed by detecting isolated points, lines and edges, which were known as edge detection techniques. Results: A particular class of segmentation techniques is based on multi resolution analysis. The image segmentation process is includes various techniques like Threshold method, boundary tracking, Clustering, Region-Based. Conclusion: The objective of this study is to provide brief study on various segmentation methodologies for the researchers. This study presents the brief review on image segmentation and analyses the performance and improvement of various algorithms and fulfilled the objectives.