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Optimization of data acquisition in axial CT under the framework of sampling on lattice for suppression of aliasing artifacts with algorithmic detector interlacing
Author(s) -
Xie Huiqiao,
Tang Xiangyang
Publication year - 2017
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.12618
Subject(s) - imaging phantom , detector , interpolation (computer graphics) , optical transfer function , iterative reconstruction , sampling (signal processing) , image resolution , interlacing , aliasing , pixel , projection (relational algebra) , computer science , image quality , computer vision , data acquisition , optics , artificial intelligence , algorithm , physics , undersampling , image (mathematics) , operating system
Purpose We present the methodology for analyzing and optimizing the sampling structure of projection data acquisition in axial multidetector CT ( MDCT ) and cone beam CT ( CBCT ) under the framework of sampling on lattice. Specifically, we propose and evaluate the scheme of interlaced detector cell binning for suppression of longitudinal aliasing artifacts. In addition, we investigate the proposed scheme's capability of mitigating shift variation in spatial resolution and possibility of improving CB image reconstruction accuracy. Methods Under the framework of sampling on lattice, the proposed scheme is evaluated using an axial MDCT with its architecture similar to that of state‐of‐the‐art CT scanners for diagnostic imaging in the clinic. The widely used FDK algorithm is adopted for image reconstruction, in which either horizontal/latitudinal or vertical/longitudinal interpolation is used for lining‐up of projection data between interlaced detector cells. Using a spiral clock phantom, the capability of suppressing aliasing artifacts and possibility of improving reconstruction accuracy is quantitatively investigated. The in‐plane spatial resolution, as assessed by the modulation transfer function ( MTF ), and its shift‐variant property are quantitatively assessed using wire phantoms, while the through‐plane spatial resolution and its shift‐variant behavior are assessed by the slice sensitivity profile ( SSP ) using thin foil phantoms. Results The preliminary results show that the interlaced detector cell binning can suppress longitudinal aliasing artifacts effectively, while the shift variation in spatial resolution and reconstruction inaccuracy can be mitigated moderately. In addition, the direction, along which the interpolation is carried out to line up projection data between the interlaced detector cells for image reconstruction, plays a significant role in determining the in‐plane and through‐plane spatial resolution. Conclusions The scheme of interlaced detector cell binning with longitudinal interpolation for data lining‐up is an effective solution for suppression of longitudinal aliasing artifacts in axial MDCT and CBCT .