Automated analysis of breast parenchymal patterns in whole breast ultrasound images: preliminary experience |
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| Authors: | Yuji Ikedo Takako Morita Daisuke Fukuoka Takeshi Hara Gobert Lee Hiroshi Fujita Etsuo Takada Tokiko Endo |
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| Institution: | (1) Department of Surgical Oncology, School of Medical practice and public health, University of Newcastle, Newcastle Mater Misericordiae Hospital, Locked Bag No. 7, Hunter Region Mail Centre, Warabrook, N.S.W, 2310, Australia;(2) Department of Radiology, Addenbrooke’s Hospital, Cambridge Breast Unit, Cambridge, UK;(3) Medical Radiation Science, School of Health Sciences, University of Newcastle, Warabrook, N.S.W, Australia |
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| Abstract: | Purpose A computerized classification scheme to recognize breast parenchymal patterns in whole breast ultrasound (US) images was developed.
A preliminary evaluation of the system performance was performed.
Methods Breast parenchymal patterns were classified into three categories: mottled pattern (MP), intermediate pattern (IP), and atrophic
pattern (AP). Each classification was defined as proposed by an experienced physician. A total of 281 image features were
extracted from a volume of interest which was automatically segmented. Canonical discriminant analysis with stepwise feature
selection was employed for the classification of the parenchymal patterns.
Results The classification scheme accuracy was computed to be 83.3% (10/12 cases) in MP cases, 91.7% (22/24 cases) in IP cases, 92.9%
(13/14 cases) in AP cases, and 90.0% (45/50 cases) in all the cases.
Conclusions The feasibility of an automated ultrasonography classifier for parenchymal patterns was demonstrated with promising results
in whole breast US images. |
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| Keywords: | Ultrasonographic breast parenchymal pattern Whole breast ultrasound Computerized classification Canonical discriminant analysis |
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