Technical note: Correction of geometric X-ray image intensifier distortion based on digital image correlation.

X-ray image intensifiers (XRIIs) inevitably produce images suffering from geometric distortion. Presently, various local and global methods exist to correct for these distortions. However, the performance of global methods is limited for dominant local distortions, and local methods tend to suffer from patch discontinuity and are generally sensitive to noise. In this paper, a novel local method is presented based on digital image correlation (DIC), which does not suffer from patch discontinuity and noise. As DIC is a very accurate and robust technique to analyze deformations, it is our candidate of choice to outperform existing correction methods. The performance of our technique was first validated through distortion simulations. Next, it was validated experimentally for four different orientations of the XRII. A theoretical study on images suffering from a simulated distortion (including noise and blurring) yielded corrections with an average accuracy of (0.20 ± 0.04) pixels. We obtained experimental data with our 14" XRII (292 mm field of view), suffering from a maximum distortion between 9.6 mm and 12.9 mm, and an average distortion between (4.4 ± 1.3) mm and (6.1 ± 2.5) mm over the image field for the different orientations. For an adequate choice of the facet size in the DIC analysis (greater than 40 pixels), the weighted mean residual error of our method varied between (0.037 ± 0.003) mm and (0.054 ± 0.003) mm, regardless of the XRII orientation. The maximum residual error varied between 0.081 mm and 0.185 mm. From the simulations, we concluded that the proposed technique is affected by neither Gaussian noise nor blurring. Furthermore, it is shown that our method can reach an accuracy that is on par with or better than the current standard tools. The novel method is fast, requires minimal operator intervention and can be fully automated.

[1]  S Rudin,et al.  Super-global distortion correction for a rotational C-arm x-ray image intensifier. , 1999, Medical physics.

[2]  Angelo Cappello,et al.  A global method based on thin-plate splines for correction of geometric distortion: an application to fluoroscopic images. , 2003, Medical physics.

[3]  Shiju Yan,et al.  Improving accuracy of XRII image distortion correction using a new hybrid image processing method: performance assessment. , 2011, Medical physics.

[4]  Luis F. Gutiérrez,et al.  A practical global distortion correction method for an image intensifier based x-ray fluoroscopy system. , 2008, Medical physics.

[5]  Shiju Yan,et al.  A method based on moving least squares for XRII image distortion correction. , 2007, Medical physics.

[6]  N. Pallikarakis,et al.  A novel approach for distortion correction for X-ray image intensifiers. , 2003, Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society.

[7]  E. Gronenschild,et al.  The accuracy and reproducibility of a global method to correct for geometric image distortion in the x-ray imaging chain. , 1997, Medical physics.

[8]  Tianmiao Wang,et al.  New method for geometric calibration and distortion correction of conventional C-arm , 2014, Comput. Biol. Medicine.

[9]  Gianluca Tozzi,et al.  The use of digital image correlation in the biomechanical area: a review , 2016 .

[10]  E. Gronenschild,et al.  Correction for geometric image distortion in the x-ray imaging chain: local technique versus global technique. , 1999, Medical physics.

[11]  Hubert W. Schreier,et al.  Image Correlation for Shape, Motion and Deformation Measurements: Basic Concepts,Theory and Applications , 2009 .

[12]  R Fahrig,et al.  Three-dimensional computed tomographic reconstruction using a C-arm mounted XRII: correction of image intensifier distortion. , 1997, Medical physics.

[13]  Anand Asundi,et al.  Two-dimensional digital image correlation for in-plane displacement and strain measurement: a review , 2009 .

[14]  W. F. Ranson,et al.  Determination of displacements using an improved digital correlation method , 1983, Image Vis. Comput..

[15]  Nicole Fruehauf,et al.  Radiologic Science For Technologists Physics Biology And Protection , 2016 .

[16]  D. B. Baier,et al.  X-ray reconstruction of moving morphology (XROMM): precision, accuracy and applications in comparative biomechanics research. , 2010, Journal of experimental zoology. Part A, Ecological genetics and physiology.

[17]  P. A. Skundberg Radiologic Science for Technologists: Physics, Biology, and Protection. 6th ed , 1998 .

[18]  A. L. Camp,et al.  Swimming muscles power suction feeding in largemouth bass , 2015, Proceedings of the National Academy of Sciences.