A 2D Synthesized Image Improves the 3D Search for Foveated Visual Systems.
A 2D Synthesized Image Improves the 3D Search for Foveated Visual Systems.
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2D 合成图像改进了注视点视觉系统的 3D 搜索。
DOI：
10.1109/tmi.2023.3246005
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发表时间：
2023
影响因子：
10.6
通讯作者：
Eckstein,MiguelP
中科院分区：
文献类型：
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作者：
Klein,DeviS;Lago,MiguelA;Abbey,CraigK;Eckstein,MiguelP
目前的医学成像越来越依赖于三维体积数据，这使得放射科医生很难彻底搜索体积的所有区域。在某些应用中（例如，数字乳房断层合成），体积数据通常与从相应的3D体积生成的合成2D图像（2D- s）配对。我们研究了这种图像配对如何影响对空间大小信号的搜索。观察者在3D卷，2D-S图像中搜索这些信号，同时观看两者。我们假设，观察者视觉外围较低的空间敏锐度阻碍了对3D图像中小信号的搜索。然而，包含2D-S引导眼球运动到可疑位置，提高观察者在3D中发现信号的能力。行为学结果表明，与单独使用3D相比，将2D-S作为体积数据的辅助工具，可以提高对小（但不是大）信号的定位和检测。同时也减少了搜索错误。为了在计算层面上理解这一过程，我们实现了一个注视点搜索模型（FSM），该模型执行人眼运动，然后根据图像中的点与注视点的偏心率，以不同的空间细节处理图像中的点。FSM预测人类对这两种信号的表现，并在2D-S补充3D搜索时捕获搜索错误的减少。我们的实验和建模结果描述了2D-S在3D搜索中的效用——通过将注意力引导到感兴趣的区域，有效减少错误，减少低分辨率外围处理的有害影响。
Current medical imaging increasingly relies on 3D volumetric data making it difficult for radiologists to thoroughly search all regions of the volume. In some applications (e.g., Digital Breast Tomosynthesis), the volumetric data is typically paired with a synthesized 2D image (2D-S) generated from the corresponding 3D volume. We investigate how this image pairing affects the search for spatially large and small signals. Observers searched for these signals in 3D volumes, 2D-S images, and while viewing both. We hypothesize that lower spatial acuity in the observers’ visual periphery hinders the search for the small signals in the 3D images. However, the inclusion of the 2D-S guides eye movements to suspicious locations, improving the observer’s ability to find the signals in 3D. Behavioral results show that the 2D-S, used as an adjunct to the volumetric data, improves the localization and detection of the small (but not large) signal compared to 3D alone. There is a concomitant reduction in search errors as well. To understand this process at a computational level, we implement a Foveated Search Model (FSM) that executes human eye movements and then processes points in the image with varying spatial detail based on their eccentricity from fixations. The FSM predicts human performance for both signals and captures the reduction in search errors when the 2D-S supplements the 3D search. Our experimental and modeling results delineate the utility of 2D-S in 3D search—reduce the detrimental impact of low-resolution peripheral processing by guiding attention to regions of interest, effectively reducing errors.