Global Visual Processing In The Lab And In The Clinic

描述(由申请人提供)：拟议的研究试图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，我们将调查全局处理是否有能力限制，以及它是否是医学图像理解任务中未得到充分利用的部分。最近的行为学研究表明，在刺激开始的200毫秒内，观察者可以从图像中提取统计和结构规律(例如，这个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规则来回答有关场景(海滩、城市街道等)的分类状态或场景中是否存在某些类别的对象(动物、车辆)的问题。这种全局图像处理通常被描述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。第一个目标是提出一系列心理物理研究，以测量观察者在观看真实世界场景时任何时候可获得的全局非选择性图像属性的数量。我们的第二个假设是，全局图像处理是专家在各种专门搜索任务中报告的目标存在的弥散感的基础。第二个目标是进行实验，以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，以支持医生执行医学图像处理。我们将收集关于“第一次猜测”对简单呈现的图像的反应的准确性的数据。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联的全局特征。一旦提取，这些全局属性将被测试它们在辅助和/或培训放射学筛查员方面的效用。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，还包括快速获取图像的全局结构和统计规则。对全球非选择性视觉处理的更好理解有望对加强癌症筛查培训计划和开发支持专业诊断专业知识的计算机辅助系统产生重要的健康后果。

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.