What do radiologists look for? Advances and limitations of perceptual learning in radiologic search.
What do radiologists look for? Advances and limitations of perceptual learning in radiologic search.
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DOI：
10.1167/jov.20.10.17
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发表时间：
2020-10-01
影响因子：
1.8
通讯作者：
Martinez-Conde S
中科院分区：
文献类型：
--
作者：
Alexander RG;Waite S;Macknik SL;Martinez-Conde S
在住院医师培训计划的指导下，放射科医生通过查看数千张医学图像来学习临床相关的视觉特征。然而，放射科专家在临床实践中使用的精确视觉特征仍然未知。识别这些特征将允许开发针对放射学培训优化和减少医疗错误的感知学习训练方法。在这里，我们回顾了试图弥合目前的差距，重点是计算显着性模型的特点和预测的凝视行为在放射科医生的理解。在准确预测图像中的相关医学信息方面已经取得了长足的进步，从而促进了新型计算机辅助检测和诊断工具的开发。在某些情况下，计算模型已经达到了与放射科医生相当的灵敏度，这表明我们可能接近于识别放射科医生使用的潜在视觉表示。然而，由于相关的自下而上的功能在任务背景和成像模式中各不相同，因此在完全理解放射学中的感知专业知识之前，还需要识别相关的自上而下的因素。沿着这些方面取得的进展将改善用于教育新一代放射科医生的工具，并有助于检测医学相关信息，最终改善患者健康。
Supported by guidance from training during residency programs, radiologists learn clinically relevant visual features by viewing thousands of medical images. Yet the precise visual features that expert radiologists use in their clinical practice remain unknown. Identifying such features would allow the development of perceptual learning training methods targeted to the optimization of radiology training and the reduction of medical error. Here we review attempts to bridge current gaps in understanding with a focus on computational saliency models that characterize and predict gaze behavior in radiologists. There have been great strides toward the accurate prediction of relevant medical information within images, thereby facilitating the development of novel computer-aided detection and diagnostic tools. In some cases, computational models have achieved equivalent sensitivity to that of radiologists, suggesting that we may be close to identifying the underlying visual representations that radiologists use. However, because the relevant bottom-up features vary across task context and imaging modalities, it will also be necessary to identify relevant top-down factors before perceptual expertise in radiology can be fully understood. Progress along these dimensions will improve the tools available for educating new generations of radiologists, and aid in the detection of medically relevant information, ultimately improving patient health.
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影响因子：
1.8
作者：
Alexander RG;Zelinsky GJ
通讯作者：
Zelinsky GJ
影响因子：
19.7
作者：
Beam, CA;Conant, EF;Sickles, EA
通讯作者：
Sickles, EA
影响因子：
9.2
作者：
Frank, Sebastian M.;Qi, Andrea;Watanabe, Takeo
通讯作者：
Watanabe, Takeo
影响因子：
1.8
作者：
BALL, K;SEKULER, R
通讯作者：
SEKULER, R
影响因子：
2
作者：
Alexander, Robert G.;Schmidt, Joseph;Zelinsky, Gregory J.
通讯作者：
Zelinsky, Gregory J.