A framework of modeling detector systems for computed tomography simulations

Ultimate development in computed tomography (CT) technology may be a system that can provide images with excellent lesion conspicuity with the patient dose as low as possible. Imaging simulation tools have been cost-effectively used for these developments and will continue. For a more accurate and realistic imaging simulation, the signal and noise propagation through a CT detector system has been modeled in this study using the cascaded linear-systems theory. The simulation results are validated in comparisons with the measured results using a laboratory flat-panel micro-CT system. Although the image noise obtained from the simulations at higher exposures is slightly smaller than that obtained from the measurements, the difference between them is reasonably acceptable. According to the simulation results for various exposure levels and additive electronic noise levels, x-ray quantum noise is more dominant than the additive electronic noise. The framework of modeling a CT detector system suggested in this study will be helpful for the development of an accurate and realistic projection simulation model.

[1]  Ehsan Samei,et al.  A method for modifying the image quality parameters of digital radiographic images. , 2003, Medical physics.

[2]  A. Fenster,et al.  A "stochastic" convolution that describes both image blur and image noise using linear-systems theory , 1995, Proceedings of 17th International Conference of the Engineering in Medicine and Biology Society.

[3]  H. Alkadhi,et al.  Evolution in Computed Tomography: The Battle for Speed and Dose , 2015, Investigative radiology.

[4]  Jong Hyo Kim,et al.  Realistic simulation of reduced-dose CT with noise modeling and sinogram synthesis using DICOM CT images. , 2013, Medical physics.

[5]  W P Segars,et al.  Realistic CT simulation using the 4D XCAT phantom. , 2008, Medical physics.

[6]  Gyuseong Cho,et al.  Cascade Modeling of Pixelated Scintillator Detectors for X-Ray Imaging , 2008, IEEE Transactions on Nuclear Science.

[7]  Jesse Tanguay,et al.  The role of x-ray Swank factor in energy-resolving photon-counting imaging. , 2010, Medical physics.

[8]  Ernst J. Rummeny,et al.  Validation of a Low Dose Simulation Technique for Computed Tomography Images , 2014, PloS one.

[9]  J. Fessler,et al.  Modelling the physics in the iterative reconstruction for transmission computed tomography , 2013, Physics in medicine and biology.

[10]  R. K. Swank Absorption and noise in x‐ray phosphors , 1973 .

[11]  W. Kalender,et al.  Combining deterministic and Monte Carlo calculations for fast estimation of scatter intensities in CT , 2006, Physics in medicine and biology.

[12]  Min Kook Cho,et al.  Performance characterization of microtomography with complementary metal-oxide-semiconductor detectors for computer-aided defect inspection , 2009 .

[13]  Ho Kyung Kim,et al.  Optical crosstalk in CT detectors and its effects on CT images , 2014, Medical Imaging.

[14]  Bruno De Man,et al.  An outlook on x-ray CT research and development. , 2008, Medical physics.

[15]  Seungman Yun,et al.  Effect of the phosphor screen optics on the Swank noise performance in indirect-conversion x-ray imaging detectors , 2014 .

[16]  Shuai Leng,et al.  Electronic noise in CT detectors: Impact on image noise and artifacts. , 2013, AJR. American journal of roentgenology.

[17]  Shuai Leng,et al.  Reducing Image Noise in Computed Tomography (CT) Colonography: Effect of an Integrated Circuit CT Detector , 2014, Journal of computer assisted tomography.

[18]  Kyle J Myers,et al.  An energy- and depth-dependent model for x-ray imaging. , 2004, Medical physics.

[19]  Ho Kyung Kim,et al.  Physics-based modeling of computed tomography systems , 2015, Medical Imaging.

[20]  Kyle J Myers,et al.  Lubberts effect in columnar phosphors. , 2004, Medical physics.

[21]  Qiu Wang,et al.  A low dose simulation tool for CT systems with energy integrating detectors. , 2013, Medical physics.