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Image Understanding from Experts' Eyes by Modeling Perceptual Skill of Diagnostic Reasoning Processes

机译:通过模拟诊断推理过程的感知技能,从专家的眼睛看图像

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Eliciting and representing experts' remarkable perceptual capability of locating, identifying and categorizing objects in images specific to their domains of expertise will benefit image understanding in terms of transferring human domain knowledge and perceptual expertise into image-based computational procedures. In this paper, we present a hierarchical probabilistic framework to summarize the stereotypical and idiosyncratic eye movement patterns shared within 11 board-certified dermatologists while they are examining and diagnosing medical images. Each inferred eye movement pattern characterizes the similar temporal and spatial properties of its corresponding segments of the experts' eye movement sequences. We further discover a subset of distinctive eye movement patterns which are commonly exhibited across multiple images. Based on the combinations of the exhibitions of these eye movement patterns, we are able to categorize the images from the perspective of experts' viewing strategies. In each category, images share similar lesion distributions and configurations. The performance of our approach shows that modeling physicians' diagnostic viewing behaviors informs about medical images' understanding to correct diagnosis.
机译:引出和代表专家的显着感知能力,在他们专业领域的域名的图像中定位,识别和分类对象将在将人体领域知识和感知专业知识转移到基于形象的计算程序方面的图像理解。在本文中,我们提出了一种分层概率框架,总结了在11个板认证的皮肤科医生内共享的陈规定型和特质眼球运动模式,同时检查和诊断医学图像。每个推断的眼睛运动模式表征其对应于专家眼睛运动序列的相应段的类似时间和空间特性。我们进一步发现了跨多个图像通常呈现的独特眼球运动模式的子集。根据这些眼球运动模式的展览的组合,我们能够将图像从专家观看策略的角度分开。在每个类别中,图像共享类似的病变分布和配置。我们的方法的表现表明,建模的医生诊断观察行为通知医学图像的理解正确诊断。

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