Computer-Aided Diagnosis Based on Speckle Patterns in Ultrasound Images

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

研究成果: 雜誌貢獻文章同行評審

21 引文 斯高帕斯(Scopus)

摘要

For breast ultrasound, the scatterer number density from backscattered echo was demonstrated in previous research to be a useful feature for tumor characterization. To take advantage of the scatterer number density in B-mode images, spatial compound imaging was obtained, and the statistical properties of speckle patterns were analyzed in this study for use in distinguishing between benign and malignant lesions. A total of 137 breast masses (95 benign cases and 42 malignant cases) were used in the proposed computer-aided diagnosis (CAD) system. For each mass, the average number of speckle pixels in a region of interest (ROI) was calculated to use the concept of scatterer number density. In addition, the first-order and second-order statistics of the speckle pixels were quantified to obtain the distributions of the pixel values and the spatial relations among the pixels. The performance of the speckle features extracted from each ROI was compared with the performance of the segmentation features extracted from each segmented tumor. As a result, the proposed CAD system using the speckle features achieved an accuracy of 89.1% (122/137); a sensitivity of 81.0% (34/42); and a specificity of 92.6% (88/95). All of the differences between the speckle features and the segmentation features are not statistically significant (p > 0.05). In a receiver operating characteristic (ROC) curve analysis, the Az value, area under ROC curve, of the speckle features was significantly better than the Az value of the segmentation features (0.93 vs. 0.86, p = 0.0359). The performance of this approach supports the notion that the speckle patterns induced by the scatterers in tissues can provide information for classifying tumors. The proposed speckle features, which were extracted readily from drawing an ROI without any preprocessing, also provide a more efficient classification approach than tumor segmentation.
原文英語
頁(從 - 到)1251-1261
頁數11
期刊Ultrasound in Medicine and Biology
38
發行號7
DOIs
出版狀態已發佈 - 七月 2012
對外發佈

ASJC Scopus subject areas

  • 放射學、核子醫學和影像學
  • 放射與超音波技術
  • 生物物理學

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