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Please use this identifier to cite or link to this item: http://hdl.handle.net/2328/26250

Title: Classifying breast masses in volumetric whole breast ultrasound data: a 2.5-dimensional approach
Authors: Lee, Gobert N
Okada, Toshiaki
Fukuoka, Daisuke
Muramatsu, Chisako
Hara, Takeshi
Morita, Takako
Takada, Etsuo
Endo, Tokiko
Fujita, Hiroshi
Keywords: Ultrasound
Breast cancer
Classification
Geometric feature
Echo feature
Issue Date: 2010
Publisher: Springer
Citation: Lee, G.N., Okada, T., Fukuoka, D., Muramatsu, C., Hara, T., Morita, T., Takada, E., Endo, T., & Fujita, H., 2010. Classifying breast masses in volumetric whole breast ultrasound data: a 2.5-dimensional approach. Digital Mammography: 10th International Workshop on Digital Mammography, LNCS 6136, 636-642.
Abstract: The aim of this paper is to investigate a 2.5-dimensional approach in classifying masses as benign or malignant in volumetric anisotropic voxel whole breast ultrasound data. In this paper, the term 2.5-dimensional refers to the use of a series of 2-dimensional images. While mammography is very effective in breast cancer screening in general, it is less sensitive in detecting breast cancer in younger women or women with dense breasts. Breast ultrasonography does not have the same limitation and is a valuable adjunct in breast cancer detection. The current study focuses on a new 2.5-dimensional approach in analyzing the volumetric whole breast ultrasound data for mass classification.
URI: http://hdl.handle.net/2328/26250
ISSN: 0302-9743
Appears in Collections:Computer Science, Engineering and Mathematics - Collected Works

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