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Journal Article 4D digital tomosynthesis image reconstruction using brute force-based adaptive total variation (BF-ATV) in a prototype LINAC system
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Authors
Sunghoon Choi, Sooyeul Lee, Young-Nam Kang, Scott S Hsieh, Hee-Joung Kim
Issue Date
2019-05
Citation
Physics in Medicine & Biology, v.64, no.9, pp.1-15
ISSN
0031-9155
Publisher
Institute of Physics (IOP)
Language
English
Type
Journal Article
DOI
https://dx.doi.org/10.1088/1361-6560/ab0d50
Abstract
Respiratory-correlated cone-beam CT (CBCT) not only inhibits rapid scanning due to the slow speed of the LINAC head gantry rotation, but its implementation for routine patient imaging is impractical because of the high radiation dose delivered during the process. Digital tomosynthesis (DTS) is a potentially faster technique that delivers a much lower radiation dose by reducing the number of projections in a limited angular range. Unfortunately, 4D-DTS introduces strong aliasing artifacts in the reconstructed images due to the sparsely sampled projections in each respiratory phase bin. The authors hereby suggest a novel low-dose 4D-DTS image reconstruction method that achieves a compromise between the occurrence of aliasing artifacts and image smoothing using a brute force-based adaptive weighting parameter searching technique. We used a prototype LINAC system mounted with a flat-panel detector to acquire tomosynthesis projections of respiratory motion in a phantom in the anterior-posterior (AP) and lateral views. Three different 4D-DTS image reconstruction schemes that included conventional filtered back-projection (FBP), adaptive steepest descent projection onto convex sets (ASD-POCS), and the proposed brute force-based adaptive total variation (BF-ATV) were implemented in four different respiratory phase bins for both AP and lateral views. All reconstructions were accelerated using a single GPU card to reduce the computation time. To study the performance of the algorithm under various sparse conditions, we operated the prototype system in three different gantry sweep modes. The results indicate that the proposed BF-ATV method yields the largest structural similarities in the differenced image between the ground-truth dataset acquired using the slow gantry sweep mode and the sparse dataset from both moderate and fast sweep modes. In addition, the proposed method maintained the object sharpness with less streaking lines and small loss of sharpness compared to the conventional FBP and ASD-POCS methods. In conclusion, the proposed low-dose 4D-DTS reconstruction scheme may provide better performance due in part to its rapid scanning. Therefore, it is potentially applicable to practical 4D imaging for radiotherapy.
KSP Keywords
4D imaging, ASD-POCS, Adaptive total variation, Anterior-posterior, Back projection(BP), Brute-force, Digital tomosynthesis(DTS), Force-based, Ground-Truth dataset, Image Smoothing, Image reconstruction