Modeling eye movement patterns to characterize perceptual skill in image-based diagnostic reasoning processes.
Modeling eye movement patterns to characterize perceptual skill in image-based diagnostic reasoning processes.
复制标题
DOI：
10.1016/j.cviu.2016.03.001
复制
发表时间：
2016-10
影响因子：
4.5
通讯作者：
Haake, Anne R.
中科院分区：
文献类型：
--
作者：
Li, Rui;Shi, Pengcheng;Pelz, Jeff;Alm, Cecilia O.;Haake, Anne R.
关键词：
专家具有在特定于其专业领域的图像中定位、感知组织、识别和分类对象的卓越能力。在本文中，我们提出了一个分层概率框架，以发现特定专业群体所表现出的刻板和特殊的观看行为。通过这些模式化的眼动行为，我们能够从在医学图像的诊断推理过程中记录眼动的受试者那里获取特定领域的知识和感知技能。分析专家的眼球运动模式使我们能够深入了解用于解决复杂感知推理任务的认知策略。进行了一项实验，收集三组不同水平或未受过医学培训的受试者（十一名经过委员会认证的皮肤科医生、四名接受培训的皮肤科医生和十三名本科生）的眼球运动和言语叙述数据，同时他们检查和描述 50 张皮肤病摄影图像。我们使用隐马尔可夫模型来描述每个受试者的眼动序列，并结合分层随机过程来捕获和区分三组内和之间的多个受试者所共享的已发现的眼动模式。独立专家对转录的口头叙述中的诊断概念性思维单元的注释与发现的眼动模式在时间上保持一致，以帮助解释这些模式的含义。通过将眼球运动模式映射到思维单元，我们揭示了推理和感知过程的视觉和语言元素之间的关系，并展示了这些受试者在解析图像时改变其行为的方式。我们还表明，推断的眼球运动模式表征了相似的时间和空间属性组，并指定了通常在多个图像中展示的独特眼球运动模式的子集。根据这些眼动模式出现的组合，我们能够以一种新颖的方式从专家观看策略的角度对图像进行分类。在每个类别中，图像都具有相似的病变分布和配置。我们的结果表明，使用代表医生的诊断观看行为和思维过程的多模态数据进行建模是可行的且信息丰富的，可以深入了解医生的认知策略以及医学图像理解。
Experts have a remarkable capability of locating, perceptually organizing, identifying, and categorizing objects in images specific to their domains of expertise. In this article, we present a hierarchical probabilistic framework to discover the stereotypical and idiosyncratic viewing behaviors exhibited with expertise-specific groups. Through these patterned eye movement behaviors we are able to elicit the domain-specific knowledge and perceptual skills from the subjects whose eye movements are recorded during diagnostic reasoning processes on medical images. Analyzing experts’ eye movement patterns provides us insight into cognitive strategies exploited to solve complex perceptual reasoning tasks. An experiment was conducted to collect both eye movement and verbal narrative data from three groups of subjects with different levels or no medical training (eleven board-certified dermatologists, four dermatologists in training and thirteen undergraduates) while they were examining and describing 50 photographic dermatological images. We use a hidden Markov model to describe each subject’s eye movement sequence combined with hierarchical stochastic processes to capture and differentiate the discovered eye movement patterns shared by multiple subjects within and among the three groups. Independent experts’ annotations of diagnostic conceptual units of thought in the transcribed verbal narratives are time-aligned with discovered eye movement patterns to help interpret the patterns’ meanings. By mapping eye movement patterns to thought units, we uncover the relationships between visual and linguistic elements of their reasoning and perceptual processes, and show the manner in which these subjects varied their behaviors while parsing the images. We also show that inferred eye movement patterns characterize groups of similar temporal and spatial properties, and specify a subset of distinctive eye movement patterns which are commonly exhibited across multiple images. Based on the combinations of the occurrences of these eye movement patterns, we are able to categorize the images from the perspective of experts’ viewing strategies in a novel way. In each category, images share similar lesion distributions and configurations. Our results show that modeling with multi-modal data, representative of physicians’ diagnostic viewing behaviors and thought processes, is feasible and informative to gain insights into physicians’ cognitive strategies, as well as medical image understanding.
登录
查看更多内容
DOI：
10.1016/j.compmedimag.2008.12.002
发表时间：
2009-04-01
影响因子：
5.7
作者：
Gordon, Shiri;Lotenberg, Shelly;Greenspan, Hayit
通讯作者：
Greenspan, Hayit
DOI：
10.1109/34.730558
发表时间：
1998-11-01
影响因子：
23.6
作者：
Itti, L;Koch, C;Niebur, E
通讯作者：
Niebur, E
影响因子：
3.5
作者：
Henderson, John M.;Malcolm, George L.;Schandl, Charles
通讯作者：
Schandl, Charles
影响因子：
6.4
作者：
Hoffman, Robert R.;Fiore, Stephen M.
通讯作者：
Fiore, Stephen M.
影响因子：
2
作者：
DeAngelus, Marianne;Pelz, Jeff B.
通讯作者：
Pelz, Jeff B.