Automatic Selection of Representative Slice From Cine-Loops of Real-Time Sonoelastography for Classifying Solid Breast Masses
作者: Yeun-Chung ChangMin-Chun YangChiun-Sheng HuangShao-Chien ChangGuan-Ying HuangWoo Kyung MoonRuey-Feng Chang
作者单位: 1Department of Medical Imaging, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan
2Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan
3Department of Surgery, National Taiwan University Hospital and National Taiwan, University College of Medicine, Taipei, Taiwan
4Department of Radiology, Seoul National University Hospital, Korea
5Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan
刊名: Ultrasound in Medicine & Biology, 2011, Vol.37 (5), pp.709-718
来源数据库: Elsevier Journal
DOI: 10.1016/j.ultrasmedbio.2011.02.007
关键词: Breast ultrasonographySonoelastographyComputer-assisted diagnosis
原始语种摘要: Abstract(#br)This study aimed to evaluate the performance of automatic selection of representative slice from cine-loops of real-time sonoelastography for classifying benign and malignant breast masses. This retrospective study included 141 ultrasound elastographic studies (93 benign and 48 malignant masses). A novel computer-assisted system was developed for the automatic segmentation of the targeted lesion from cine-loops of real-time sonoelastography. Its hard ratio, defined as the ratio of the number of hard pixels within the tumor divided by the total number of pixels of the whole tumor, was also calculated. The targeted mass was segmented by edge-detection and region growing methods, with combined motion registration after manually defining the original seed. Signal-to-noise ratio (...
全文获取路径: Elsevier  (合作)
影响因子:2.455 (2012)

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