Task-Based Image Quality Assessment in X-Ray Computed Tomography

Abstract

In X-Ray CT, there is always a desire to maintain the image quality while reducing the radiation dose. Recently several dose reduction approaches in both software and hardware have been developed to achieve the goal of making radiation as low as possible. Thus, the assessment of image quality becomes an important factor for routine quality control of medical X-Ray devices. In this work, task-based image quality measurements using model observers were used to evaluate the performance of X-Ray CT systems. To evaluate the dose reduction ability, detection tasks as well as combined detection and estimation tasks were considered. In detection tasks and combined detection and estimation tasks, the channelized Hotelling observer (CHO) and channelized scanning linear observer (CSLO) (with Dense Difference of Gauss channels) were employed respectively. They were used to evaluate the dose reduction capability of the iterative reconstruction algorithm developed by GE compared to the traditional reconstruction algorithm, filtered backprojection (FBP). Additionally, CHO and CSLO were also used for optimization of CT protocols. Our methods were also applied to Cardiac CT systems for temporal resolution evaluations. Two reconstruction algorithms, FBP and the motion correction algorithm, Snapshot Freeze (SSF), operated at two heart-beating rates with two reconstruction windows were quantitatively evaluated using task-based measurements. Finally, due to the huge demand of data acquisitions in the conventional channelized model observers, a proposed High-Dose-Signal-LOOL CHO/CSLO (HL-CHO/CSLO) that could efficiently reduce the data requirement has also been investigated in the pure detection, and combined detection and estimation task. In all studies, the practicality and the use of real data is emphasized. The results of all these studies demonstrate the usefulness of the task-based measurements of image quality in X-Ray CT imaging.