Malignant and benign breast tissue classification performance using a scatterer structure preclassifier.

Kevin D Donohue; Lexun Huang; Georgia Georgiou; Fernand S Cohen; Catherine W Piccoli; Flemming Forsberg

doi:10.1109/tuffc.2003.1209562

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Malignant and benign breast tissue classification performance using a scatterer structure preclassifier.

Kevin D Donohue·Lexun Huang·Georgia Georgiou·Fernand S Cohen·Catherine W Piccoli·Flemming Forsberg

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Abstract

Benign and malignant breast tissue classification is examined for generalized-spectrum parameters computed from RF ultrasound data when a preclassification of subregions based on general scattering properties is performed. Results using a clinical database of 84 patients show statistically significant improvements (over 10% in receiver operation characteristic (ROC) areas) when only coherent scatterer subregions are used as compared to using all subregions within the region of interest.

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Algorithms Breast Neoplasms Humans Image Interpretation, Computer-Assisted Predictive Value of Tests Quality Control ROC Curve Reproducibility of Results Scattering, Radiation Ultrasonography, Mammary Evaluation Study Letter Research Support, U.S. Gov't, P.H.S.Validation Study

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Kevin D Donohue, Lexun Huang, Georgia Georgiou, Fernand S Cohen, Catherine W Piccoli, Flemming Forsberg. 2003. Malignant and benign breast tissue classification performance using a scatterer structure preclassifier.. https://doi.org/10.1109/tuffc.2003.1209562

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