Computer‐aided diagnosis using morphological features for classifying breast lesions on ultrasound

• Published in: Ultrasound in obstetrics & gynecology 2008-09, Vol.32 (4), p.565-572
• Main Authors: Huang, Y.‐L., Chen, D.‐R., Jiang, Y.‐R., Kuo, S.‐J., Wu, H.‐K., Moon, W. K.
• Format: Article
• Language: English
• Subjects: Adult; Aged; Algorithms; Biological and medical sciences; breast cancer; Breast Neoplasms - diagnostic imaging; breast sonography; computer‐aided diagnosis; Diagnosis, Computer-Assisted - methods; Diagnosis, Differential; Female; Gynecology. Andrology. Obstetrics; Humans; Image Interpretation, Computer-Assisted - methods; Mammary gland diseases; Medical sciences; Middle Aged; morphological analysis; Principal Component Analysis; support vector machine; tumor classification; tumor segmentation; Tumors; Ultrasonography, Mammary - methods; Young Adult
• ISSN: 0960-7692; 1469-0705
• DOI: 10.1002/uog.5205

Objectives To develop and evaluate a computer‐aided diagnosis (CAD) system with automatic contouring and morphological analysis to aid in the classification of breast tumors using ultrasound. Methods We evaluated 118 breast lesions (34 malignant and 84 benign tumors). Each tumor contour was automatically extracted from the digitized ultrasound image. Nineteen practical morphological features from the extracted contour were calculated and principal component analysis (PCA) was applied to find independent features. A support vector machine (SVM) classifier utilized the selected principal vectors to identify the breast tumor as benign or malignant. In this study, all the cases were sampled with k‐fold cross‐validation (k = 10) to evaluate the performance by receiver–operating characteristics (ROC) curve analysis. Results The areas under the ROC curves for the proposed CAD systems using all morphological features and the lower‐dimensional principal vector were 0.91 and 0.90, respectively. The classification ability for breast tumors using morphological information was good. Conclusions This system differentiates benign from malignant breast tumors well and therefore provides a clinically useful second opinion. Moreover, the morphological features are nearly setting‐independent and thus available to various ultrasound machines. Copyright © 2008 ISUOG. Published by John Wiley & Sons, Ltd.