Improve spatial resolution by Modeling Finite Focal Spot (MFFS) for industrial CT reconstruction.

The finite focal spot is one of the major limitations of the high spatial resolution CT, especially to the high-energy industrial CT system with a macro-focus x-ray source. In this paper, we propose an efficient reconstruction framework through finite focal spot size based projection modeling to improve the spatial resolution of current industrial CT system, and demonstrate the superior performance of this method. First of all, the blurred projection produced by a finite size source is modeled as the integral ideal projection of a given point source over the finite focal spot support. Under the model discretization, the approximate linear equivalence relation between the actual finite focus model and the ideal point source model is established. Then a projection recovery method with this relationship is presented to recover the projection of the finer focal spot from the blurred projection. Finally, a high-spatial resolution image can be reconstructed from the recovered projections using the standard Filtered Back-Projection (FBP) algorithm. Furthermore the noise in the reconstructed image with different model parameters is studied and a difference image based fusion method is presented for the further suppression of the noise caused by the projection analysis processing. Both numerical simulations and real experiments have shown that the proposed reconstruction framework with the outstanding performance and efficiency characteristics can significantly enhance the spatial resolutions of current high-energy industrial CT systems.

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

[2]  Jochen Hiller,et al.  A computer simulation platform for the estimation of measurement uncertainties in dimensional X-ray computed tomography , 2012 .

[3]  Stephen Rudin,et al.  Overcoming x-ray tube small focal spot output limitations for high resolution region of interest imaging , 2012, Medical Imaging.

[4]  S. Carmignato,et al.  Accuracy of industrial computed tomography measurements: Experimental results from an international comparison , 2012 .

[5]  Yining Zhu,et al.  An approach to increasing the resolution of industrial CT images based on an aperture collimator. , 2013, Optics express.

[6]  Hengyong Yu,et al.  Finite detector based projection model for high spatial resolution. , 2012, Journal of X-ray science and technology.

[7]  Jochen Hiller,et al.  Physical characterization and performance evaluation of an x-ray micro-computed tomography system for dimensional metrology applications , 2012 .

[8]  Javier Santillan,et al.  Precise 3D dimensional metrology using high-resolution x-ray computed tomography (μCT) , 2010, Optical Engineering + Applications.

[9]  Volkmar Schulz,et al.  FPGA-based singles and coincidences processing pipeline for integrated digital PET/MR detectors , 2012, 2012 IEEE Nuclear Science Symposium and Medical Imaging Conference Record (NSS/MIC).

[10]  M. V. Yester,et al.  Geometrical Limitations Of Computed Tomography (CT) Scanner Resolution , 1977, Other Conferences.

[11]  Lin Fu,et al.  Sinogram rebinning and frequency boosting for high resolution iterative CT reconstruction with focal spot deflection , 2014, Medical Imaging.

[12]  Jiang Hsieh,et al.  Enhancement of in-plane spatial resolution in volumetric Computed Tomography with focal spot wobbling - overcoming the constraint on number of projection views per gantry rotation. , 2010, Journal of X-ray science and technology.

[13]  Michael Grasruck,et al.  Characterization of focal spots of x-ray tubes in CT systems: method development and examples , 2010, Medical Imaging.

[14]  Marc Kachelrieß,et al.  Effects of ray profile modeling on resolution recovery in clinical CT. , 2014, Medical physics.

[15]  Philipp Krämer,et al.  Computed tomography in quality control: chances and challenges , 2013 .

[16]  Benoit M. Dawant,et al.  Medical Imaging 2010: Physics of Medical Imaging , 2010 .

[17]  Michael Salamon,et al.  Comparison of different methods for determining the size of a focal spot of microfocus X-ray tubes , 2008 .

[18]  A. Weckenmann,et al.  Multi-energy image stack fusion in computed tomography , 2010 .

[19]  J. Liu Simple technique for measurements of pulsed Gaussian-beam spot sizes. , 1982, Optics letters.

[20]  Robert Schmitt,et al.  Computed tomography for dimensional metrology , 2011 .

[21]  Xiaochuan Pan,et al.  Sampling and aliasing consequences of quarter-detector offset use in helical CT , 2004, IEEE Transactions on Medical Imaging.

[22]  P. J. Bourdillon Application of Optical Instrumentation in Medicine , 1977 .

[23]  Xun Jia,et al.  Relationship between x-ray illumination field size and flat field intensity and its impacts on x-ray imaging. , 2012, Medical physics.

[24]  Eduard Gröller,et al.  Surface Extraction from Multi-Material Components for Metrology using Dual Energy CT , 2007, IEEE Transactions on Visualization and Computer Graphics.

[25]  M. P. Morigi,et al.  Application of X-ray Computed Tomography to Cultural Heritage diagnostics , 2010 .

[26]  Wim Dewulf,et al.  Industrial computer tomography for dimensional metrology: Overview of influence factors and improvement strategies , 2009 .

[27]  Bruno De Man,et al.  Enhancement of spatial resolution in model-based iterative CT reconstruction by using sinogram preprocessing filters , 2012, 2012 IEEE Nuclear Science Symposium and Medical Imaging Conference Record (NSS/MIC).