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Eye Movements as an Index of Pathologist Visual Expertise: A Pilot Study

机译:眼动作为病理学家视觉专长的指标:一项初步研究

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摘要

A pilot study examined the extent to which eye movements occurring during interpretation of digitized breast biopsy whole slide images (WSI) can distinguish novice interpreters from experts, informing assessments of competency progression during training and across the physician-learning continuum. A pathologist with fellowship training in breast pathology interpreted digital WSI of breast tissue and marked the region of highest diagnostic relevance (dROI). These same images were then evaluated using computer vision techniques to identify visually salient regions of interest (vROI) without diagnostic relevance. A non-invasive eye tracking system recorded pathologists’ (N = 7) visual behavior during image interpretation, and we measured differential viewing of vROIs versus dROIs according to their level of expertise. Pathologists with relatively low expertise in interpreting breast pathology were more likely to fixate on, and subsequently return to, diagnostically irrelevant vROIs relative to experts. Repeatedly fixating on the distracting vROI showed limited value in predicting diagnostic failure. These preliminary results suggest that eye movements occurring during digital slide interpretation can characterize expertise development by demonstrating differential attraction to diagnostically relevant versus visually distracting image regions. These results carry both theoretical implications and potential for monitoring and evaluating student progress and providing automated feedback and scanning guidance in educational settings.
机译:一项前瞻性研究检查了在数字化乳腺活检全玻片图像(WSI)解释过程中发生的眼球运动可在多大程度上区分新手解释者和专家,从而评估了培训期间以及整个医师学习过程中对能力发展的评估。一位接受过乳房病理学研究培训的病理学家解释了乳腺组织的数字WSI,并标出了最高诊断相关性(dROI)区域。然后使用计算机视觉技术对这些相同的图像进行评估,以识别没有诊断意义的视觉显着的目标区域(vROI)。一个非侵入式的眼动追踪系统记录了病理学家在图像解释期间的(N = 7)视觉行为,并且我们根据他们的专业水平对vROI与dROI的差异进行了测量。相对于专家而言,在解释乳腺病理学方面专业知识相对较低的病理学家更有可能专注于诊断无关的vROI,并随后返回。反复固定注意力不集中的vROI在预测诊断失败方面显示出有限的价值。这些初步结果表明,在数字幻灯片解释期间发生的眼球运动可以通过证明对诊断相关的图像区域和视觉上分散注意力的图像区域的差异吸引来表征专业知识的发展。这些结果具有理论意义和潜力,可用于监视和评估学生的学习进度,并在教育环境中提供自动反馈和扫描指导。

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