Global Visual Processing In The Lab And In The Clinic

描述（由申请人提供）：拟议的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全球处理，如果它是一个未充分利用的组成部分的医学图像理解任务。最近的行为研究表明，在刺激开始的200 ms内，观察者可以提取图像中的统计和结构特征（例如，这种显示的平均大小或方向是什么？）即使视觉选择性注意力集中在另一个视觉任务上。他们还可以使用这些工具来回答有关场景（海滩、城市街道等）的类别状态或场景中某些类别对象（动物、车辆）的存在的问题。这种全局图像处理通常被描绘为具有基本上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。第一个目标提出了一系列的心理物理学研究，将衡量全球非选择性的图像属性的数量提供给观察者在任何一个时间观看真实的世界场景。我们的第二个假设是，全球图像处理的基础上的扩散感的目标存在的专家报告，在各种专门的搜索任务。第二个目标提出了实验，以评估放射学筛查中病理学感觉的可靠性，其目标是开发能够支持医生执行医学图像处理的适当的培训程序和/或系统。我们将收集关于对简要呈现的图像的“第一猜测”响应的准确性的数据。这些数据将输入到全局场景处理计算模型，该模型将提取与正常和异常图像相关的全局特征。一旦被提取，这些全局属性将被测试其在辅助和/或培训放射学筛查人员中的效用。相关性：在许多情况下，我们理解复杂视觉图像的能力不仅包括仔细检查图像，还包括快速访问图像的全局结构和统计特征。提高对全球非选择性视觉处理的理解，可以预期将有重要的健康后果，无论是在癌症筛查的培训计划的加强和计算机辅助系统的发展，支持专业诊断的专业知识。

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.