Review and Evaluation of Medical Image Segmentation Using Methods of Optimal Filtering

摘要

Image segmentation is an important process of image analysis. It consists of subdividing an image into its constituent parts and extracting these interesting parts. A large variety of segmentation algorithms have been developed. The evaluation and comparison of these algorithms turns out to be important and even indispensable for correctly using them. This paper presents an objective study of segmentation algorithms using the methods of optimal filtering. This study is distinguished from other studies by its consideration of both evaluation and comparison, treating both image cases (noisy and non-noisy ones). The results of implementation, an evaluation of the advantages and the drawbacks of each one of them, and a study of their immunity towards three types of noise are also presented. All these characteristics make this study a general and effective one for revealing the performance of segmentation algorithms using the methods of optimal filtering.