LAUSR

HighlightsAn adaptive filtering is introduced into a computer‐aided diagnosis (CAD) system to highlight the characteristic of breast tumors detected in screening ultrasound (US).The adaptive filtering enhances the CAD system to emphasize the meaningfulness of tumor size, allows a new regularization technique to be embedded, and increasing the classification accuracy.For the classification between malignant and benign tumors with two kinds of tumor size (Symbol1 cm and Symbol1 cm), especially in the tumors larger or equal to 1 cm, the proposed CAD was more robust than conventional CAD. Symbol. No caption available. Symbol. No caption available.The CAD system using various quantitative US features would provide a promising diagnostic suggestion for classifying the breast tumors detected at screening US images. Abstract Screening ultrasound (US) is increasingly used as a supplement to mammography in women with dense breasts, and more than 80% of cancers detected by US alone are 1 cm or smaller. An adaptive computer‐aided diagnosis (CAD) system based on tumor size was proposed to classify breast tumors detected at screening US images using quantitative morphological and textural features. In the present study, a database containing 156 tumors (78 benign and 78 malignant) was separated into two subsets of different tumor sizes (Symbol1 cm and Symbol1 cm) to explore the improvement in the performance of the CAD system. After adaptation, the accuracies, sensitivities, specificities and Az values of the CAD for the entire database increased from 73.1% (114/156), 73.1% (57/78), 73.1% (57/78), and 0.790 to 81.4% (127/156), 83.3% (65/78), 79.5% (62/78), and 0.852, respectively. In the data subset of tumors larger than 1 cm, the performance improved from 66.2% (51/77), 68.3% (28/41), 63.9% (23/36), and 0.703 to 81.8% (63/77), 85.4% (35/41), 77.8% (28/36), and 0.855, respectively. The proposed CAD system can be helpful to classify breast tumors detected at screening US.