Quantitative ultrasound analysis for classification of BI-RADS category 3 breast masses

Woo Kyung Moon, Chung Ming Lo, Jung Min Chang, Chiun Sheng Huang, Jeon Hor Chen, Ruey Feng Chang

研究成果: 雜誌貢獻文章同行評審

41 引文 斯高帕斯(Scopus)

摘要

The accuracy of an ultrasound (US) computer-aided diagnosis (CAD) system was evaluated for the classification of BI-RADS category 3, probably benign masses. The US database used in this study contained 69 breast masses (21 malignant and 48 benign masses) that at blinded retrospective interpretation were assigned to BI-RADS category 3 by at least one of five radiologists. For computer-aided analysis, multiple morphology (shape, orientation, margin, lesions boundary, and posterior acoustic features) and texture (echo patterns) features based on BI-RADS lexicon were implemented, and the binary logistic regression model was used for classification. The receiver operating characteristic curve analysis was used for statistical analysis. The area under the curve (Az) of morphology, texture, and combined features were 0.90, 0.75, and 0.95, respectively. The combined features achieved the best performance and were significantly better than using texture features only (0.95 vs. 0.75, p value = 0.0163). The cut-off point at the sensitivity of 86 % (18/21), 95 % (20/21), and 100 % (21/21) achieved the specificity of 90 % (43/48), 73 % (35/48), and 33 % (16/48), respectively. In conclusion, the proposed CAD system has the potential to be used in upgrading malignant masses misclassified as BI-RADS category 3 on US by the radiologists.
原文英語
頁(從 - 到)1091-1098
頁數8
期刊Journal of Digital Imaging
26
發行號6
DOIs
出版狀態已發佈 - 12月 2013
對外發佈

ASJC Scopus subject areas

  • 放射與超音波技術
  • 放射學、核子醫學和影像學
  • 電腦科學應用

指紋

深入研究「Quantitative ultrasound analysis for classification of BI-RADS category 3 breast masses」主題。共同形成了獨特的指紋。

引用此