Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/12440
Title: Fuzzy Image Segmentation for Mass Detection in Digital Mammography: Recent Advances and Techniques
Contributor(s): Alharbi, Hajar Mohammedsaleh H (author); Kwan, Paul H  (author); Jayawardena, Ashoka  (author); Sajeev, Abudulkadir  (author)
Publication Date: 2012
DOI: 10.4018/978-1-4666-1830-5.ch021
Handle Link: https://hdl.handle.net/1959.11/12440
Abstract: In the last decade, many computer-aided diagnosis (CAD) systems that utilize a broad range of diagnostic techniques have been proposed. Due to both the inherently complex structure of the breast tissues and the low intensity contrast found in most mammographic images, CAD systems that are based on conventional techniques have been shown to have missed malignant masses in mammographic images that would otherwise be treatable. On the other hand, systems based on fuzzy image processing techniques have been found to be able to detect masses in cases where conventional techniques would have failed. In the current chapter, recent advances in fuzzy image segmentation techniques as applied to mass detection in digital mammography are reviewed. Image segmentation is an important step in CAD systems since the quality of its outcome will significantly affect the processing downstream that can involve both detection and classification of benign versus malignant masses.
Publication Type: Book Chapter
Source of Publication: Multidisciplinary Computational Intelligence Techniques: Applications in Business, Engineering and Medicine, p. 378-402
Publisher: Information Science Reference
Place of Publication: Hershey, United States of America
ISBN: 9781466618329
9781466618312
9781466618305
Fields of Research (FoR) 2008: 080109 Pattern Recognition and Data Mining
080108 Neural, Evolutionary and Fuzzy Computation
080106 Image Processing
Fields of Research (FoR) 2020: 461199 Machine learning not elsewhere classified
460203 Evolutionary computation
460306 Image processing
Socio-Economic Objective (SEO) 2008: 890201 Application Software Packages (excl. Computer Games)
970108 Expanding Knowledge in the Information and Computing Sciences
970111 Expanding Knowledge in the Medical and Health Sciences
Socio-Economic Objective (SEO) 2020: 220401 Application software packages
280115 Expanding knowledge in the information and computing sciences
HERDC Category Description: B1 Chapter in a Scholarly Book
Publisher/associated links: http://trove.nla.gov.au/work/163586506
Series Name: Premier Reference Source
Editor: Editor(s): Shawkat Ali, Noureddine Abbadeni and Mohamed Batouche
Appears in Collections:Book Chapter

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