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Scatter correction for a clinical cone‐beam CT system using an optimized stationary beam blocker in a single scan
Author(s) -
Liang Xiaokun,
Jiang Yangkang,
Zhao Wei,
Zhang Zhicheng,
Luo Chen,
Xiong Jing,
Yu Shaode,
Yang Xiaoming,
Sun Jihong,
Zhou Qinxuan,
Niu Tianye,
Xie Yaoqin
Publication year - 2019
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1002/mp.13568
Subject(s) - hounsfield scale , imaging phantom , cone beam computed tomography , projection (relational algebra) , image quality , beam (structure) , image resolution , iterative reconstruction , optics , image guided radiation therapy , nuclear medicine , medical imaging , materials science , computer science , artificial intelligence , physics , medicine , image (mathematics) , algorithm , radiology , computed tomography
Purpose Scatter contamination in the cone‐beam CT (CBCT) leads to CT number inaccuracy, spatial nonuniformity, and loss of image contrast. In our previous work, we proposed a single scan scatter correction approach using a stationary partial beam blocker. Although the previous method works effectively on a tabletop CBCT system, it fails to achieve high image quality on a clinical CBCT system mainly due to the wobble of the LINAC gantry during scan acquisition. Due to the mechanical deformation of CBCT gantry, the wobbling effect is observed in the clinical CBCT scan, and more missing data present using the previous blocker with the uniformly distributed lead strips. Methods An optimal blocker distribution is proposed to minimize the missing data. In the objective function of the missing data, the motion of the beam blocker in each projection is estimated using the segmentation due to its high contrast in the blocked area. The scatter signals from the blocker are also estimated using an air scan with the inserted blocker. The final image is generated using the forward projection to compensate for the missing data. Results On the Catphan©504 phantom, our approach reduces the average CT number error from 86 Hounsfield unit (HU) to 9 HU and improves the image contrast by a factor of 1.45 in the high‐contrast rods. On a head patient, the CT number error is reduced from 97 HU to 6 HU in the soft‐tissue region and the image spatial nonuniformity is decreased from 27% to 5%. Conclusions The results suggest that the proposed method is promising for clinical applications.