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		<doi>10.1109/SIBGRAPI.2008.10</doi>
		<citationkey>FerrariHillPlewMart:2008:CaBiAs</citationkey>
		<title>Can bilateral asymmetry analysis of breast MR images provide additional information for detection of breast diseases?</title>
		<format>Printed, On-line.</format>
		<year>2008</year>
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		<author>Ferrari, Ricardo J.,</author>
		<author>Hill, Kimberley A.,</author>
		<author>Plewes, Donald B.,</author>
		<author>Martel, Anne L.,</author>
		<affiliation>University Health Network - University of Toronto, Toronto, ON, Canada</affiliation>
		<affiliation>Division of Medical Oncology, Department of Medicine, Toronto, ON, Canada</affiliation>
		<affiliation>Imaging Research, Sunnybrook Health Sciences Centre / Department of Biophysics, Toronto, ON, Canada</affiliation>
		<affiliation>Imaging Research, Sunnybrook Health Sciences Centre / Department of Biophysics, Toronto, ON, Canada</affiliation>
		<editor>Jung, Cláudio Rosito,</editor>
		<editor>Walter, Marcelo,</editor>
		<conferencename>Brazilian Symposium on Computer Graphics and Image Processing, 21 (SIBGRAPI)</conferencename>
		<conferencelocation>Campo Grande, MS, Brazil</conferencelocation>
		<date>12-15 Oct. 2008</date>
		<publisher>IEEE Computer Society</publisher>
		<publisheraddress>Los Alamitos</publisheraddress>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Full Paper</tertiarytype>
		<transferableflag>1</transferableflag>
		<versiontype>finaldraft</versiontype>
		<keywords>breast cancer, breast MRI, Phase Congruency, log-Gabor.</keywords>
		<abstract>This paper presents a new method for bilateral asym- metry analysis of breast MR images that uses directional statistics of the breast parenchymal edges, obtained from a multiresolution local energy edge detector, and image texture information derived from local energy maps, ob- tained by using a bank of log-Gabor filters. Classification of MRI scans into cancer and non-cancer categories was per- formed by linear discriminant analysis and the leave-one- out methodology. A total of 40 cases, 20 normal/benign (BI-RADS 1 and 2) and 20 malignant, taken from a high risk screening population, were used in this pilot study. Av- erage classification accuracy of 70% (&#954; = 0.45 ± 0.14) with sensitivity and specificity of 75% and 65%, respec- tively, was achieved. The results obtained support the idea that bilateral asymmetry analysis of breast MR images can provide additional information for detection of breast tissue changes arising from diseases.</abstract>
		<language>en</language>
		<targetfile>ferrari-BilateralAsymmetry.pdf</targetfile>
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