Single-photon emission computed tomography (SPECT) is a modality widely used to detect myocardial ischemia and myocardial infarction. Objectively assessing and comparing different SPECT systems is important so that the best detectability of cardiac defects can be achieved. Whitaker, Clarkson, and Barrett's study on the scanning linear observer (SLO) shows that the SLO can be used to estimate the location and size of signals. One major advantage of the SLO is that it can be used with projection data rather than reconstruction data. Thus, this observer model assesses overall hardware performance independent by any reconstruction algorithm. In addition, we will show that the run time of image-quality studies is significantly reduced. Several systems derived from the GE CZT-based dedicated cardiac SPECT camera Discovery 530c design, which is officially named the Alcyone Technology: Discovery NM 530c, were assessed using the performance of the SLO for the task of detecting cardiac defects and estimating the properties of the defects. Clinically, hearts can be virtually segmented into three coronary artery territories: left anterior descending artery (LAD), left circumflex artery (LCX), and right coronary artery (RCA). One of the most important functions of a cardiac SPECT system is to produce images from which a radiologist can correctly predict in which territory the defect exists. A good estimation of the defect extent from the images is also very helpful for determining the seriousness of the myocardial ischemia. In this dissertation, both locations and extent of defects were estimated by the SLO, and system performance was assessed using localization receiver operating characteristic (LROC) / estimation receiver operating characteristic (EROC) curves. Area under LROC curve (AULC) / area under EROC curve (AUEC) and true positive fraction (TPF) at specific false positive fraction (FPF) can be treated as the figures of merit (FOMs). As the results will show, a combination of the SLO and LROC / EROC curves can determine the configuration that has the most estimation/detection information and thus is a useful method for assessing cardiac SPECT systems.

Maintaining or even improving image quality while lowering patient dose is always the desire in clinical computed tomography (CT) imaging. Iterative reconstruction (IR) algorithms have been designed to allow for a reduced dose while maintaining or even improving an image. However, we have previously shown that the dose-saving capabilities allowed with IR are different for different clinical tasks. The channelized scanning linear observer (CSLO) was applied to study clinical tasks that combine detection and estimation when assessing CT image data. The purpose of this work is to illustrate the importance of task complexity when assessing dose savings and to move toward more realistic tasks when performing these types of studies. Human-observer validation of these methods will take place in a future publication. Low-contrast objects embedded in body-size phantoms were imaged multiple times and reconstructed by filtered back projection (FBP) and an IR algorithm. The task was to detect, localize, and estimate the size and contrast of low-contrast objects in the phantom. Independent signal-present and signal-absent regions of interest cropped from images were channelized by the dense-difference of Gauss channels for CSLO training and testing. Estimation receiver operating characteristic (EROC) curves and the areas under EROC curves (EAUC) were calculated by CSLO as the figure of merit. The one-shot method was used to compute the variance of the EAUC values. Results suggest that the IR algorithm studied in this work could efficiently reduce the dose by similar to 50% while maintaining an image quality comparable to conventional FBP reconstruction warranting further investigation using real patient data. (C) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.