Abstract
Interpretation of volumetric medical images represents a rapidly growing proportion of the workload in radiology. However, relatively little is known about the strategies that best guide search behavior when looking for abnormalities in volumetric images. Although there is extensive literature on two-dimensional medical image perception, it is an open question whether the conclusions drawn from these images can be generalized to volumetric images. Importantly, volumetric images have distinct characteristics (e.g., scrolling through depth, smooth-pursuit eye-movements, motion onset cues, etc.) that should be considered in future research. In this manuscript, we will review the literature on medical image perception and discuss relevant findings from basic science that can be used to generate predictions about expertise in volumetric image interpretation. By better understanding search through volumetric images, we may be able to identify common sources of error, characterize the optimal strategies for searching through depth, or develop new training and assessment techniques for radiology residents.
Highlights
Volumetric medical imaging, such as computed tomography (CT), magnetic resonance imaging (MRI), or digital breast tomosynthesis (DBT), helps retain the 3D nature of the body’s internal structures by stacking multiple cross-sectional images
1) What are the stimulus properties that guide attention in volumetric medical images? 2) What are common sources of error in volumetric medical image interpretation? 3) What are the consequences of increased cognitive load and how can they be overcome? 4) What are the best strategies for searching through depth across different tasks and modalities? 5) How are scene regularities learned in volumetric images? 6) What are the characteristics of expertise in volumetric image interpretation? 7) What are the consequences of limited memory in volumetric image search? 8) How do radiologists decide to terminate search in large volumetric images? 9) How do motor and perceptual processes interact in the evaluation of volumetric images?
Concluding remarks and future directions This review of the literature highlights the many contributions made by researchers toward better understanding volumetric image interpretation
Summary
Volumetric medical imaging, such as CT, magnetic resonance imaging (MRI), or digital breast tomosynthesis (DBT), helps retain the 3D nature of the body’s internal structures by stacking multiple cross-sectional images. Abnormalities are sometimes very small relative to the overall size of the image To illustrate this point, Rubin (2015) calculated that lung cancer nodules between 4. We will discuss nine research areas that we feel best represent the current priorities of the field (Table 1) In each of these sections, we will discuss relevant findings from the basic science and medical image perception literatures and highlight promising areas for future research. We direct the reader to existing resources that cover this topic in depth (Rubin, Drew, & Williams, 2018; Venjakob & Mello-Thoms, 2015) Rather, this manuscript is a selected review of the literature on volumetric image perception through the lens of basic research on visual attention and memory. Many of these topics undoubtedly pertain to 2D imaging as well, the primary intent of this
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