Global Visual Processing In The Lab And In The Clinic

描述（由申请人提供）：本研究旨在阐明非选择性全局图像处理在正常视觉感知和医学图像处理中的作用。特别是，我们将调查是否有能力限制的整体处理，如果它是一个未充分利用的医学图像理解任务的组成部分。最近的行为研究表明，即使视觉选择注意力集中在另一个视觉任务上，在刺激开始的200 ms内，观察者也可以提取图像的统计和结构规律（例如，这个显示的平均大小或方向是什么？）。他们还可以使用这些规律来回答关于场景（海滩，城市街道等）的分类状态或场景中某些类别物体（动物，车辆）的存在的问题。这种全局图像处理通常被描述为基本上具有无限的能力来执行其特定任务。然而，我们的假设是，它的能力是有限的。第一个目标是提出一系列的心理物理学研究，这些研究将测量观察者在观看真实世界场景时任何时候可用的全局非选择性图像属性的数量。我们的第二个假设是，在各种专门的搜索任务中，专家报告说，全局图像处理是目标存在的扩散感的基础。第二个目标是通过实验来评估放射学筛查中病理感觉的可靠性，目的是开发适当的培训计划和/或系统，以支持医生进行医学图像处理。我们将收集对简要呈现的图像的“第一猜测”反应的准确性数据。这些数据将作为全局场景处理计算模型的输入，该模型将提取与正常和异常图像相关的全局特征。一旦提取出来，将测试这些全局属性在辅助和/或培训放射筛查人员方面的效用。相关性：在许多情况下，我们理解复杂视觉图像的能力不仅涉及对图像的仔细审查，还涉及对图像的全局结构和统计规律的快速访问。提高对全局非选择性视觉处理的理解，可以预期对癌症筛查培训计划的加强和支持专业诊断技术的计算机辅助系统的发展具有重要的健康影响。

DESCRIPTION (provided by applicant): The proposed research seeks to illuminate the role of non-selective global image processing in normal visual perception and in medical image processing. In particular, we will investigate whether there are capacity limits to global processing and if it is an under-utilized component of the medical image understanding task. Recent behavioral studies demonstrate that within 200 ms of stimulus onset, observers can extract statistical and structural regularities in images (e.g. what is the mean size or orientation of this display?) even if visual selective attention is focused on another visual task. They can also use those regularities to answer questions about the categorical status of scenes (beach, urban street, etc) or the presence in the scene of some categories of objects (animal, vehicle). This global image processing is often portrayed as having essentially unlimited capacity to perform its particular tasks. However, our hypothesis is that its capacity is limited. The first aim proposes a series of psychophysical studies that will measure the number of global non-selective image properties available to observers at any one time when viewing real world scenes. Our second hypothesis is that global image processing underlies the diffuse sense of target presence reported by experts in a variety of specialized search tasks. The second aim proposes experiments to assess the reliability of the sense of pathology in radiology screening with the goal of developing adequate training programs and/or systems that can support physicians performing medical image processing. We will collect data on the accuracy of "first guess" responses to briefly presented images. Those data will be the input to a global scene processing computational model that will extract global features associated with normal and abnormal images. Once extracted, these global properties will be then tested for their utility in aiding and/or training radiology screeners. Relevance: In many cases, our ability to understand complex visual images not only involves careful scrutinizing of that image, but also rapid access to global structural and statistical regularities of the image. An improved understanding of global non-selective visual processing can be expected to have important health consequences for both the enhancement of training programs in cancer screening and the development of computer aided systems supporting professional diagnostic expertise.