Influence of the Computer-Aided Decision Support System Design on Ultrasound-Based Breast Cancer Classification.

ABSTRACT: Automation of medical data analysis is an important topic in modern cancer diagnostics, aiming at robust and reproducible workflows. Therefore, we used a dataset of breast US images (252 malignant and 253 benign cases) to realize and compare different strategies for CAD support in lesion detection and classification. Eight different datasets (including pre-processed and spatially augmented images) were prepared, and machine learning algorithms (i.e., Viola-Jones; YOLOv3) were trained for lesion detection. The radiomics signature (RS) was derived from detection boxes and compared with RS derived from manually obtained segments. Finally, the classification model was established and evaluated concerning accuracy, sensitivity, specificity, and area under the Receiver Operating Characteristic c

SUBMITTER: Magnuska ZA 

PROVIDER: S-EPMC8773857 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature