自动化学报2016，Vol.42Issue(4)：580-592,13.DOI:10.16383/j.aas.2016.c150199
基于多域先验的乳腺超声图像协同分割
Breast Ultrasound Image Co-segmentation by Means of Multiple-domain Knowledge
摘要
Abstract
Because of low signal-noise ratio, low contrast and blurry boundaries, breast ultrasound (BUS) image segmen-tation is quite challenging. In this paper, a multiple-domain knowledge based co-segmentation model is proposed for BUS segmentation. It combines spatial and frequency domain prior knowledge and introduces the idea of co-segmentation to segment BUS sequence. First, tumor poses, position and intensity distribution are modeled to constrain the segmentation in the spatial domain, and then the phase feature and zero-crossing feature in the frequency domain. Finally, the BUS sequence segmentation is formulated as a co-segmentation problem. Experimental results show that the proposed method can handle low contrast and hypoechoic BUS images well and segment BUS accurately.关键词
乳腺超声图像/协同分割/多域先验/计算机辅助诊断Key words
Breast ultrasound (BUS) images/co-segmentation/multiple-domain knowledge/computer-aided diagnosis (CAD)引用本文复制引用
邵昊阳,张英涛,鲜敏,李致勋,唐降龙..基于多域先验的乳腺超声图像协同分割[J].自动化学报,2016,42(4):580-592,13.基金项目
国家自然科学基金(61370162)资助Supported by National Natural Science Foundation of China (61370162) （61370162）
