Techniques for Medical Image Segmentation

Author:

Lenkiewicz Przemyslaw1,Pereira Manuela2,Freire Mário M.2,Fernandes José3

Affiliation:

1. University of Beira Interior & Microsoft Portugal, Portugal

2. University of Beira Interior, Portugal

3. Microsoft Portugal, Portugal

Abstract

This chapter contains a survey of the most popular techniques for medical image segmentation that have been gaining attention of the researchers and medical practitioners since the early 1980s until present time. Those methods are presented in chronological order along with their most important features, examples of the results that they can bring and examples of application. They are also grouped into three generations, each of them representing a significant evolution in terms of algorithms’ novelty and obtainable results compared to the previous one. This survey helps to understand what have been the main ideas standing behind respective segmentation methods and how were they limited by the available technology. In the following part of this chapter several of promising, recent methods are evaluated and compared based on a selection of important features. Together with the survey from the first section this serves to show which are the directions currently taken by researchers and which of them have the potential to be successful.

Publisher

IGI Global

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Introduction;Marginal Space Learning for Medical Image Analysis;2014

2. A Comparative Study of Improved Artificial Bee Colony Algorithms Applied to Multilevel Image Thresholding;Mathematical Problems in Engineering;2013

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