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

Cited 66 time in Web of Science Cited 84 time in Scopus
Authors
Huang, Y-L; Chen, D-R; Jiang, Y-R; Kuo, S-J; Wu, H-K; Moon, W K
Issue Date
2008-04-03
Publisher
Wiley-Blackwell
Citation
Ultrasound Obstet Gynecol. 2008; 32(4): 565-572
Keywords
AdultAgedAlgorithmsBreast Neoplasms/*ultrasonographyDiagnosis, Computer-Assisted/*methodsDiagnosis, DifferentialFemaleHumansImage Interpretation, Computer-Assisted/methodsMiddle AgedPrincipal Component AnalysisUltrasonography, Mammary/*methodsYoung Adult
Abstract
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.
ISSN
1469-0705 (Electronic)
Language
English
URI
http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18383556

http://hdl.handle.net/10371/67865
DOI
https://doi.org/10.1002/uog.5205
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College of Medicine/School of Medicine (의과대학/대학원)Radiology (영상의학전공)Journal Papers (저널논문_영상의학전공)
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