Assessing image quality and dose reduction of a new x‐ray computed tomography iterative reconstruction algorithm using model observers. Issue 7 (17th June 2014)

• Record Type: Journal Article
• Authors: Tseng, Hsin‐Wu; Fan, Jiahua; Kupinski, Matthew A.; Sainath, Paavana; Hsieh, Jiang
• Is Part Of: Medical physics. Volume 41:Issue 7(2014)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2014-06-17
• Subjects: Computed tomography -- Reconstruction; computerised tomography -- image reconstruction -- iterative methods -- medical image processing; model observer -- image quality -- dose reduction -- channelized Hotelling observer -- iterative reconstruction; Computerised tomographs -- Biological material, e.g. blood, urine; Haemocytometers -- Digital computing or data processing equipment or methods, specially adapted for specific applications -- Image data processing or generation, in general; Computed tomography -- Medical image reconstruction -- Medical X‐ray imaging -- Image reconstruction -- Medical image noise -- Image quality assessment -- Dosimetry; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1118/1.4881143
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Purpose: A number of different techniques have been developed to reduce radiation dose in x‐ray computed tomography (CT) imaging. In this paper, the authors will compare task‐based measures of image quality of CT images reconstructed by two algorithms: conventional filtered back projection (FBP), and a new iterative reconstruction algorithm (IR). Methods: To assess image quality, the authors used the performance of a channelized Hotelling observer acting on reconstructed image slices. The selected channels are dense difference Gaussian channels (DDOG).A body phantom and a head phantom were imaged 50 times at different dose levels to obtain the data needed to assess image quality. The phantoms consisted of uniform backgrounds with low contrast signals embedded at various locations. The tasks the observer model performed included (1) detection of a signal of known location and shape, and (2) detection and localization of a signal of known shape. The employed DDOG channels are based on the response of the human visual system. Performance was assessed using the areas under ROC curves and areas under localization ROC curves. Results: For signal known exactly (SKE) and location unknown/signal shape known tasks with circular signals of different sizes and contrasts, the authors' task‐based measures showed that a FBP equivalent image quality can be achieved at lower dose levels using the IR algorithm. For the SKE case, the range of dose reduction is 50%–67% (head phantom) and 68%–82% (body phantom). For the study of location unknown/signal shape known, the dose reduction range can be reached at 67%–75% for head phantom and 67%–77% for body phantom case. These results suggest that the IR images at lower dose settings can reach the same image quality when compared to full dose conventional FBP images. Conclusions: The work presented provides an objective way to quantitatively assess the image quality of a newly introduced CT IR algorithm. The performance of the model observers using the IR images was always higher than that seen using the FBP images in the authors' SKE and SKE location unknown detection tasks. To achieve a FBP‐equivalent image quality in CT systems, the authors can lower the radiation dose by using this IR image reconstruction algorithm. Further studies are warranted using clinical data and human observer to validate these results for more complicated and realistic tasks.