Auto-detection algorithm of liver focus based on visual attention model

被引：0

作者：

Ma, Li ^{[1
]}

Wang, Wenfeng ^{[1
]}

机构：

[1] School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China

来源：

Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument | 2010年 / 31卷 / 03期

关键词：

Computerized tomography - Behavioral research - Computer aided diagnosis - Medical imaging - Signal detection;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

The detection of region of interest(ROI) in medical images has played a very important role in computer aided diagnosis. Because liver-focus organs have the characteristics of weak textural and small intensity differences with their neighborhood, a novel algorithm of extracting abnormal regions in liver CT images has been proposed in this paper, which uses visual attention model. Firstly, a set of statistical features related to liver textures and some salient factors based on directional fractals are selected. Then, an overall saliency map is composed from several sub-salient maps of feature components. Finally, the regions with liver focus are located by labeling the saliency map. Experiments show that the locations of liver focus regions could be found using the proposed method accurately and using saliency maps is an effective way of extracting ROI in medical images.

引用

页码：635 / 642