Image quality analysis of vibration effects in C-arm flat panel X-ray imaging

The motion of C-arm scanning X-ray systems may result in vibrations of the imaging sub-system. In this paper, we connect C-arm system vibrations to Image Quality (IQ) deterioration for 2D angiography and 3D cone beam X-ray imaging, using large Flat Panel detectors. Vibrations will affect the projected image sharpness and the projected image position. The former will appear as blur and the latter as image shift for the 2D projection radiography process. If this phenomenon is not corrected in the post processing (pixel shift), it will manifest as subtraction registration artifacts. We will model and verify the effect of vibrations in 2D subtracted and non-subtracted flat panel imaging. Two effects on 3D IQ are modeled: (1) vibrations during an actual acquisition run inducing movement blur and (2) C-arm movement calibration errors in the iso-center giving remnant blur. The model establishes a relation between vibration amplitudes and image quality for dominant system Eigen-frequencies. The validity and accuracy of the model for 2D and 3D imaging modes is supported and demonstrated by experiments and even provides sufficient quality for defining image quality requirements.

[1]  Max A. Viergever,et al.  Retrospective motion correction in digital subtraction angiography: a review , 1999, IEEE Transactions on Medical Imaging.

[2]  Ruud M. Snoeren,et al.  Image quality simulation and verification of x-ray volume imaging systems , 2006, SPIE Medical Imaging.

[3]  Franz Kainberger,et al.  Quantification and Clinical Relevance of Head Motion During Computed Tomography , 2003, Investigative radiology.

[4]  Gordon Johnston,et al.  Statistical Models and Methods for Lifetime Data , 2003, Technometrics.

[5]  Que,et al.  @bullet @bullet @bullet ® , .

[6]  D. Holdsworth,et al.  Use of a C-arm system to generate true three-dimensional computed rotational angiograms: preliminary in vitro and in vivo results. , 1997, AJNR. American journal of neuroradiology.

[7]  David A Jaffray,et al.  Accurate technique for complete geometric calibration of cone-beam computed tomography systems. , 2005, Medical physics.

[8]  Lingyun Chen,et al.  Spatial resolution properties in cone beam CT: a simulation study. , 2008, Medical physics.

[9]  Ehsan Samei,et al.  Comparison of edge analysis techniques for the determination of the MTF of digital radiographic systems , 2005, Physics in medicine and biology.

[10]  L. Feldkamp,et al.  Practical cone-beam algorithm , 1984 .

[11]  P. D. De with,et al.  High-resolution 3D X-ray imaging of intracranial nitinol stents , 2011, Neuroradiology.

[12]  Thomas Wendler,et al.  Advances in Health care Technology Care Shaping the Future of Medical , 2006 .