基于视觉感知信息的乳腺钼靶肿块检测分析与自动提取

doi:10.3969/j.issn.0258-8021. 2014.01.005

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Abstract Clinical diagnosis according to medical images is a process of radiologists’ visual perception and decisionmaking. The radiologists’ visual perception information is intimately associated with diagnosis. How to effectively use visual perception information to improve the decisionmaking accuracy in computeraided diagnosis is a research subject which is full of scientific significance and clinical value. This paper conducted researches on the analysis and the use of visual perception behavior during diagnosis to explore two issues:one is how well the single perceptual information during diagnosis can reflect masses position; the other is how to use the perceptual information for extracting masses. In the paper, the research method includes two steps. Firstly, radiologists’ fixation point sequence, in which every point includes fixation point location in mammogram, duration time and pupil diameters, was recorded by an eyetracker during reading and then clustered to achieve some radiologists’ concerns according to the three visual features. Shooting average was calculated by analyzing the positional relationship between concerns and masses in the same mammogram. Secondly, regarding concerns as seeds, the SBRG (seedsbased region growing) approach and the multiscale mass segmentation approach were applied to buckle breast masses from mammograms. The result of applying the proposed method to 75 mammograms from both DDSM and Zhejiang Cancer Hospital showed that it could achieve shooting average of 58.49% when the limitation of concerns number was 4, and the fullextraction rate for the shot masses was 70.97%. It is revealed that the perceptual information is helpful to reflect masses position as well as to understand the inner mechanism of perceptual feedback.

Key words： CAD visual perception image segmentation eyetracker clustering analysis

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http://cjbme.csbme.org/EN/ 10.3969/j.issn.0258-8021. 2014.01.005 OR http://cjbme.csbme.org/EN/Y2014/V33/I1/28