Image artefact propagation in motion estimation and reconstruction in interventional cardiac C-arm CT.
The acquisition of data for cardiac imaging using a C-arm computed tomography system requires several seconds and multiple heartbeats. Hence, incorporation of motion correction in the reconstruction step may improve the resulting image quality. Cardiac motion can be estimated by deformable three-dimensional (3D)/3D registration performed on initial 3D images of different heart phases. This motion information can be used for a motion-compensated reconstruction allowing the use of all acquired data for image reconstruction. However, the result of the registration procedure and hence the estimated deformations are influenced by the quality of the initial 3D images. In this paper, the sensitivity of the 3D/3D registration step to the image quality of the initial images is studied. Different reconstruction algorithms are evaluated for a recently proposed cardiac C-arm CT acquisition protocol. The initial 3D images are all based on retrospective electrocardiogram (ECG)-gated data. ECG-gating of data from a single C-arm rotation provides only a few projections per heart phase for image reconstruction. This view sparsity leads to prominent streak artefacts and a poor signal to noise ratio. Five different initial image reconstructions are evaluated: (1) cone beam filtered-backprojection (FDK), (2) cone beam filtered-backprojection and an additional bilateral filter (FFDK), (3) removal of the shadow of dense objects (catheter, pacing electrode, etc) before reconstruction with a cone beam filtered-backprojection (cathFDK), (4) removal of the shadow of dense objects before reconstruction with a cone beam filtered-backprojection and a bilateral filter (cathFFDK). The last method (5) is an iterative few-view reconstruction (FV), the prior image constrained compressed sensing combined with the improved total variation algorithm. All reconstructions are investigated with respect to the final motion-compensated reconstruction quality. The algorithms were tested on a mathematical phantom data set with and without a catheter and on two porcine models using qualitative and quantitative measures. The quantitative results of the phantom experiments show that if no dense object is present within the scan field of view, the quality of the FDK initial images is sufficient for motion estimation via 3D/3D registration. When a catheter or pacing electrode is present, the shadow of these objects needs to be removed before the initial image reconstruction. An additional bilateral filter shows no major improvement with respect to the final motion-compensated reconstruction quality. The results with respect to image quality of the cathFDK, cathFFDK and FV images are comparable. In conclusion, in terms of computational complexity, the algorithm of choice is the cathFDK algorithm.
Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, Martensstr 3, D-91058 Erlangen, Germany. Erlangen Graduate School in Advanced Optical Technologies (SAOT), Paul-Gordan-Str 6, D-91052 Erlangen, Germany.
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Müller
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Maier
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Schwemmer
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Lauritsch
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De Buck
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Wielandts
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Hornegger
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Fahrig
D000818:Animals; D016477:Artifacts; D055424:Cardiac-Gated Imaging Techniques; D054893:Cone-Beam Computed Tomography / Q000379:methods*; D006321:Heart / Q000000981:diagnostic imaging* / Q000502:physiology*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D009068:Movement; D019047:Phantoms, Imaging; D013552:Swine