ANALYTICAL MODELS OF DETECTION AND DISCRIMINATION

检测和辨别的分析模型

• 批准号: 2096383
• 负责人: MARIE FOLEY KIJEWSKI
• 金额: $ 20.67万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 1993
• 资助国家: 美国
• 起止时间: 1993-09-01 至 1996-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2096383
• 关键词: computer simulation; mathematical model; model design /development; performance; psychophysics; radiology; sensory signal detection

DESCRIPTION (Adapted from Applicant's Abstract): The proposed research would develop analytical models relating human performance in detection tasks to physical properties of the imaging system. The tasks to be investigated here resemble diagnostic tasks more closely than do the widely used signal-known- exactly (SKE) tasks in that they involve uncertainty about certain aspects of the signals, such as size or location. Therefore, the applicants expect that they would be more valid bases on which to design imaging systems. The proposed analytical approach generalizes detection tasks to estimation of certain parameters of the signal, such as amplitude or size. The models to be developed would be based on the Cramer-Rao (CR) and Barankin lower bounds on the precision with which the parameter of interest can be determined in the presence of uncertainty as to the values of other parameters. These bounds depend on the imaging task (i.e., which parameters are considered unknown), the signal, and the physical properties of the imaging system; they do not require specification of an estimation procedure. The bounds quantify the propagation of pixel noise into variance of the parameter estimates, incorporating the effects of nonstochastic ambiguities.Parameter estimation tasks, e.g., signal amplitude estimation, can be associated with binary tasks, e.g., signal detection. Increased variance in a parameter estimate implies decreased ideal observer signal to noise ratio (SNR) in the relevant binary task. It was proposed that increased variance in amplitude estimates due to uncertainty about the signal would be reflected in reduced human performance in detection. This hypothesis would be tested by psychophysical experiments which estimate the receiver operating characteristic (ROC) curve for human performance in the detection tasks, allowing direct comparison between human and ideal performance.

描述(改编自申请者摘要)：拟议的研究 将开发与人类在检测中的表现相关的分析模型 任务与成像系统的物理属性相关。要完成的任务 此处调查的任务与诊断任务更相似 广泛使用的信号已知(SKE)任务，因为它们涉及 信号的某些方面的不确定性，例如大小或 地点。因此，申请者预计他们会更多 设计成像系统的有效依据。建议的分析 该方法将检测任务推广到某些参数的估计 例如，信号的幅度或大小。待开发的模型 将基于Cramer-Rao(CR)和Barankin下限 中确定感兴趣的参数的精度。 其他参数值存在不确定性。这些 界限取决于成像任务(即，考虑哪些参数 未知)、信号和成像系统的物理属性； 它们不需要详细说明评估程序。这个 边界将像素噪声的传播量化为 考虑非随机性影响的参数估计 模糊性。参数估计任务，例如，信号幅度 估计可以与例如信号检测的二进制任务相关联。 参数估计中的方差增加意味着理想值降低 相关二进制任务中的观察者信噪比(SNR)。它 建议增加幅度估计的方差，原因是 信号的不确定性将反映在人类活动的减少 在检测方面的表现。这一假设将通过以下方式进行检验 估计接收者工作情况的心理物理实验 检测任务中人类表现的特征(ROC)曲线， 允许在人类和理想表现之间进行直接比较。