Welcome to the InfoSci Platform
Fuzzy-Based Medical Image Processing

Fuzzy-Based Medical Image Processing

G. R. Sinha
Copyright: © 2016 |Pages: 16
ISBN13: 9781466687899|ISBN10: 1466687894|EISBN13: 9781466687905
DOI: 10.4018/978-1-4666-8789-9.ch030
Cite Chapter Cite Chapter

MLA

Sinha, G. R. "Fuzzy-Based Medical Image Processing." Human-Computer Interaction: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2016, pp. 666-681. https://doi.org/10.4018/978-1-4666-8789-9.ch030

APA

Sinha, G. R. (2016). Fuzzy-Based Medical Image Processing. In I. Management Association (Ed.), Human-Computer Interaction: Concepts, Methodologies, Tools, and Applications (pp. 666-681). IGI Global. https://doi.org/10.4018/978-1-4666-8789-9.ch030

Chicago

Sinha, G. R. "Fuzzy-Based Medical Image Processing." In Human-Computer Interaction: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 666-681. Hershey, PA: IGI Global, 2016. https://doi.org/10.4018/978-1-4666-8789-9.ch030

Export Reference

Mendeley
Favorite

Abstract

Medical Image Processing (MIP) is a set of tools applied over medical images, which consists of several components such as image acquisition, enhancement, segmentation, restoration, etc. The most important component of MIP is medical image segmentation used in Computer-Aided Diagnosis (CAD) systems used for detection of abnormalities in medical images. This chapter presents an overview and the importance of soft computing techniques in solving the problems of medical imaging. The authors highlight the significance of fuzzy-based clustering and similar methods for MIP and its applications. Fuzzy C-Means Clustering Method (FCM) is found the most suitable method among existing clustering methods for medical images. FCM addresses the problem of over-segmentation and helps in improvement of diagnosis accuracy. Application of optimization tool causes the reduction of execution time. A comparison of fuzzy-based methods over conventional methods suggests that neuro-fuzzy system as hybrid approach is an efficient method for medical image analysis.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.