Quantitative breast lesion classification based on multichannel distributions in shear-wave imaging
Related Experiment Video
Updated: Apr 1, 2026
Clinical Imaging of Microwave Mammography
Published on: November 14, 2025
Chung-Ming Lo1, Yi-Chen Lai2, Yi-Hong Chou2
1Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan; Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan.
Background And Objectives:
A computer-aided diagnosis (CAD) system based on the quantified color distributions in shear-wave elastography (SWE) was developed to evaluate the malignancies of breast tumors.
Methods:
For 57 benign and 31 malignant tumors, 18 SWE features were extracted from regions of interest (ROI), including the tumor and peritumoral areas. In the ROI, a histogram in each color channel was described using moments such as the mean, variance, skewness, and kurtosis. Moreover, three color channels were combined as a vector to evaluate tissue elasticity. The SWE features were then combined in a logistic regression classifier for breast tumor classification.
Results:
The performance of the CAD system achieved an accuracy of 81%. Combining the CAD system with a BI-RADS assessment obtained an Az improvement from 0.77 to 0.89 (p-value <0.05).
Conclusions:
The combination of the proposed CAD system based on SWE features and the BI-RADS assessment would provide a promising diagnostic suggestion.
