Wei, Chia-Hung and Li, Chang-Tsun (2006) Calcification descriptor and relevance feedback learning algorithms for content-based mammogram retrieval. In: 8th International Workshop on Digital Mammography, Manchester, ENGLAND, JUN 18-21, 2006. Published in: DIGITAL MAMMOGRAPHY, PROCEEDINGS, 4046 pp. 307-314.

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Abstract

In recent years a large number of digital mammograms have been generated in hospitals and breast screening centers. To assist diagnosis through indexing those mammogram databases, we proposed a content-based image retrieval framework along with a novel feature extraction technique for describing the degree of calcification phenomenon revealed in the mammograms and six relevance feedback learning algorithms, which fall in the category of query point movement, for improving system performance. The results show that the proposed system can reach a precision rate of 0.716 after five rounds of relevance feedback have been performed.

Item Type:	Conference Item (UNSPECIFIED)
Subjects:	Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
Series Name:	LECTURE NOTES IN COMPUTER SCIENCE
Journal or Publication Title:	DIGITAL MAMMOGRAPHY, PROCEEDINGS
Publisher:	SPRINGER-VERLAG BERLIN
ISBN:	3-540-35625-8
ISSN:	0302-9743
Editor:	Astley, SM and Brady, M and Rose, C and Zwiggelaar, R
Date:	2006
Volume:	4046
Number of Pages:	8
Page Range:	pp. 307-314
Publication Status:	Published
Title of Event:	8th International Workshop on Digital Mammography
Location of Event:	Manchester, ENGLAND
Date(s) of Event:	JUN 18-21, 2006
URI:	http://wrap.warwick.ac.uk/id/eprint/33154

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