Optimization-based image reconstruction from sparse-view data in offset-detector CBCT

被引:90
作者
Bian, Junguo [1 ]
Wang, Jiong [2 ]
Han, Xiao [1 ]
Sidky, Emil Y. [1 ]
Shao, Lingxiong [2 ]
Pan, Xiaochuan [1 ,3 ]
机构
[1] Univ Chicago, Dept Radiol, Chicago, IL 60637 USA
[2] Philips Healthcare, Cleveland, OH 44143 USA
[3] Univ Chicago, Dept Radiat & Cellular Oncol, Chicago, IL 60637 USA
基金
美国国家卫生研究院;
关键词
D O I
10.1088/0031-9155/58/2/205
中图分类号
R318 [生物医学工程];
学科分类号
0831 [生物医学工程];
摘要
The field of view (FOV) of a cone-beam computed tomography (CBCT) unit in a single-photon emission computed tomography (SPECT)/CBCT system can be increased by offsetting the CBCT detector. Analytic-based algorithms have been developed for image reconstruction from data collected at a large number of densely sampled views in offset-detector CBCT. However, the radiation dose involved in a large number of projections can be of a health concern to the imaged subject. CBCT-imaging dose can be reduced by lowering the number of projections. As analytic-based algorithms are unlikely to reconstruct accurate images from sparse-view data, we investigate and characterize in the work optimization-based algorithms, including an adaptive steepest descent-weighted projection onto convex sets (ASD-WPOCS) algorithms, for image reconstruction from sparse-view data collected in offset-detector CBCT. Using simulated data and real data collected from a physical pelvis phantom and patient, we verify and characterize properties of the algorithms under study. Results of our study suggest that optimization-based algorithms such as ASD-WPOCS may be developed for yielding images of potential utility from a number of projections substantially smaller than those used currently in clinical SPECT/CBCT imaging, thus leading to a dose reduction in CBCT imaging.
引用
收藏
页码:205 / 230
页数:26
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