Automated analysis of breast parenchymal patterns in whole breast ultrasound images: preliminary experience.
OBJECTIVE
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.
Ikedo
Yuji
Y
Department of Intelligent Image Information, Division of Regeneration and Advanced Medical Sciences, Graduate School of Medicine, Gifu University, Yanagido, Gifu, Japan. ikedo@fjt.info.gifu-u.ac.jp
Morita
Takako
T
Fukuoka
Daisuke
D
Hara
Takeshi
T
Lee
Gobert
G
Fujita
Hiroshi
H
Takada
Etsuo
E
Endo
Tokiko
T
D001941:Breast Diseases / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D016217:Ultrasonography, Mammary / Q000379:methods*