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