Observer Studies Involving Search: Modeling and Analysis

涉及搜索的观察者研究：建模和分析

• 批准号: 7425830
• 负责人: DEV P CHAKRABORTY
• 金额: $ 31.53万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-08-01 至 2009-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7425830
• 关键词: Accounting; Algorithms; Area; Clinical; Collaborations; Collection; Communities; Computer Assisted; Computer software; Data; Detection; Development; Diagnostic Imaging; Digital Mammography; Evaluation; Eye Movements; Figs - dietary; Image; Imaging technology; Lead; Letters; Localized Lesion; Location; Malignant neoplasm of lung; Medical Imaging; Methodology; Methods; Modality; Modeling; Numbers; Patients; Perception; Probability; Radiology Specialty; Rate; Reader; Receiver Operating Characteristics; Reporting; Research; Research Design; Research Personnel; Resources; Role; Science; Simulate; Site; Solutions; Spiral Computed Tomography; Standards of Weights and Measures; Statistical Models; System; Testing; Validation; Variant; Vision research; Work; X-Ray Computed Tomography; design; interest; lung cancer screening; models and simulation; radiologist; response; success

DESCRIPTION (provided by applicant): Since the inception of the paradigm in 1961 the analysis of FROC (free-response receiver operating characteristic) data (i.e., mark-rating pairs) has remained an unsolved problem in imaging science. Since the radiologist must search patient images for localized lesions, intrinsically FROC data is generated in virtually all imaging studies in radiology. Currently there is great interest in evaluating different computer aided detection (CAD) algorithms for lung cancer screening with helical CT scans. This task also involves search and depending on the CAD in use there are approximately 4 to 20 suspicious areas reported per patient While in the past the receiver operating characteristic (ROC) paradigm has been the standard method for the evaluation of diagnostic imaging systems, its limitation to one report per patient is now being increasingly felt. This is a proposal to develop the science and perform the requisite testing of the FROC paradigm by accomplishing the following aims. (1) Develop a statistical model for FROC data that includes the effect of search and other relevant perceptual factors and which reduces to the standard ROC model in non-search tasks. (2) Use the model to validate and evaluate currently proposed methods for analyzing location and ratings data, and in particular determine their statistical power. (3) Develop an algorithm to determine the parameters of the model from clinical FROC data and to make statistical inferences regarding the modalities being tested; verify that the estimated search parameters correlate with values inferred from eye-movement recordings. (4) Provide practical and validated software to the user community that will offer more statistical power and therefore require fewer resources of cases and readers. The significance of the proposed work is that on the scale of previous developments, the potential gain in statistical power by the FROC method is very large. Also, the explicit modeling of search and the ability to estimate search related parameters from observer data should open up new areas of vision research that all researchers can exploit.

描述（由申请人提供）： 自1961年该范例开始以来，FROC（自由响应接收器操作特性）数据的分析（即，标记-评级对）仍然是成像科学中未解决的问题。由于放射科医师必须搜索患者图像以寻找局部病变，因此本质上FROC数据在放射学中的几乎所有成像研究中生成。目前有很大的兴趣在评估不同的计算机辅助检测（CAD）算法的肺癌筛查与螺旋CT扫描。该任务还涉及搜索，并且根据所使用的CAD，每个患者报告大约4到20个可疑区域。虽然在过去，接收器工作特性（ROC）范例一直是用于评估诊断成像系统的标准方法，但现在越来越多地感觉到其对每个患者一个报告的限制。这是一个建议，以发展科学和执行必要的测试FROC范式通过实现以下目标。(1)为FROC数据开发一个统计模型，包括搜索和其他相关感知因素的影响，并在非搜索任务中简化为标准ROC模型。(2)使用该模型来验证和评估目前提出的分析位置和收视率数据的方法，特别是确定其统计能力。(3)开发一种算法，从临床FROC数据中确定模型参数，并对正在测试的模态进行统计推断;验证估计的搜索参数与从眼动记录中推断的值相关。(4)向用户社区提供实用和经过验证的软件，这些软件将提供更大的统计能力，因此需要更少的病例和读者资源。所提出的工作的意义在于，在以前的发展规模上，FROC方法在统计功效上的潜在增益是非常大的。此外，搜索的显式建模和从观察者数据中估计搜索相关参数的能力应该开辟所有研究人员都可以利用的视觉研究的新领域。