By analyzing human readers’ performance in detecting small round lesions in simulated digital breast tomosynthesis background in a location known exactly scenario, we have developed a model observer that is a better predictor of human performance with different levels of background complexity (i.e., anatomical and quantum noise). Our analysis indicates that human observers perform a lesion dete...

We estimated human observer linear templates underlying the detection of a realistic, spherical mass signal with mammographic backgrounds. Five trained naïve observers participated in two-alternative forced-choice (2-AFC) detection experiments with the signal superimposed on synthetic, clustered lumpy backgrounds (CLBs) in one condition and on nonstationary real mammographic backgrounds in anot...

Title of dissertation: TASK SPECIFIC EVALUATION METHODOLOGY FOR CLINICAL FULL FIELD DIGITAL MAMMOGRAPHY Haimo Liu, Doctor of Philosophy, 2012 Dissertation directed by: Professor Iacovos Kyprianou Department of Bioengineering Purpose: The purpose of this dissertation is to evaluate the image quality of clinical Full Field Digital Mammography (FFDM) systems. This is done by evaluating image acqui...

Synopsis This chapter presents x-ray image quality optimization techniques using digital phantom images and computerized observer models. The X-ray imaging parameters are optimized so as to maximize tumor detectability while minimizing the patient dose. Digital phantoms are generated using the virtual photographic and radiographic imaging simulator (ViPRIS) package. ViPRIS uses a tomographic ph...

Medical-imaging systems are designed to aid medical specialists in a specific task. In order to satisfy the quality preferences of a human observer, the optimization of medicalimaging systems has to include measurements of human performance and has to use these results for final tuning of the physical parameters of the system. To measure human performance it is necessary to conduct the psychoph...