Intensity-invariant texture analysis for classification of bi-rads category 3 breast masses

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

研究成果: 雜誌貢獻文章同行評審

23 引文 斯高帕斯(Scopus)

摘要

Radiologists likely incorrectly classify benign masses as Breast Imaging Reporting and Data System (BIRADS) category 3. A computer-aided diagnosis (CAD) system was developed in this study as a second viewer to avoid misclassification of carcinomas. Sixty-nine biopsy-proven BI-RADS category 3 masses, including 21 malignant and 48 benign masses, were used to evaluate the CAD system. To improve the texture features, gray-scale variations between images were reduced by transforming pixels into intensity-invariant ranklet coefficients. The textures of the tumor and speckle pixels were extracted from the transformed ranklet images to provide more robust features than in conventionalCADsystems. As a result, tumor texture and speckle texture with ranklet transformation achieved significantly better areas under the receiver operating characteristic curve (Az) compared with those without ranklet transformation (Az = 0.83 vs. 0.58 and Az = 0.80 vs. 0.56, p value <0.05). The improved CAD system can be a second reader to confirm the classification of BI-RADS category 3 masses.
原文英語
頁(從 - 到)2039-2048
頁數10
期刊Ultrasound in Medicine and Biology
41
發行號7
DOIs
出版狀態已發佈 - 2015

ASJC Scopus subject areas

  • Biophysics
  • Radiological and Ultrasound Technology
  • Acoustics and Ultrasonics

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