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Proceedings Paper

A clinical evaluation of total variation-Stokes image reconstruction strategy for low-dose CT imaging of the chest
Author(s): Yan Liu; Hao Zhang; William Moore; Priya Bhattacharji; Zhengrong Liang
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Paper Abstract

One hundred “normal-dose” computed tomography (CT) studies of the chest (i.e., 1,160 projection views, 120kVp, 100mAs) data sets were acquired from the patients who were scheduled for lung biopsy at Stony Brook University Hospital under informed consent approved by our Institutional Review Board. To mimic low-dose CT imaging scenario (i.e., sparse-view scan), sparse projection views were evenly extracted from the total 1,160 projections of each patient and the total radiation dose was reduced according to how many sparse views were selected. A standard filtered backprojection (FBP) algorithm was applied to the 1160 projections to produce reference images for comparison purpose. In the low-dose scenario, both the FBP and total variation-stokes (TVS) algorithms were applied to reconstruct the corresponding low-dose images. The reconstructed images were evaluated by an experienced thoracic radiologist against the reference images. Both the low-dose reconstructions and the reference images were displayed on a 4- megapixel monitor in soft tissue and lung windows. The images were graded by a five-point scale from 0 to 4 (0, nondiagnostic; 1, severe artifact with low confidence; 2, moderate artifact or moderate diagnostic confidences; 3, mild artifact or high confidence; 4, well depicted without artifacts). Quantitative evaluation measurements such as standard deviations for different tissue types and universal quality index were also studied and reported for the results. The evaluation concluded that the TVS can reduce the view number from 1,160 to 580 with slightly lower scores as the reference, resulting in a dose reduction to close 50%.

Paper Details

Date Published: 18 March 2015
PDF: 8 pages
Proc. SPIE 9412, Medical Imaging 2015: Physics of Medical Imaging, 94123S (18 March 2015); doi: 10.1117/12.2081614
Show Author Affiliations
Yan Liu, Stony Brook Univ. (United States)
Hao Zhang, Stony Brook Univ. (United States)
William Moore, Stony Brook Univ. (United States)
Priya Bhattacharji, Stony Brook Univ. (United States)
Zhengrong Liang, Stony Brook Univ. (United States)


Published in SPIE Proceedings Vol. 9412:
Medical Imaging 2015: Physics of Medical Imaging
Christoph Hoeschen; Despina Kontos, Editor(s)

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