Dirk Schäfer

Motion-compensated and gated cone beam filtered back-projection for 3-D rotational X-ray angiography

This paper presents a method to reconstruct moving objects from cone beam X-ray projections acquired during a single rotational run using a given motion vector field. The method is applicable to voxel driven cone-beam filtered back-projection reconstruction approaches. Here, a formulation based on the algorithm of Feldkamp, Davis, and Kress (FDK) is presented. The motion correction is applied during the back-projection step by shifting the voxel to be reconstructed according to the motion vector field. The method is applied to three-dimensional (3-D) rotational X-ray angiography. Projections from a beating coronary heart phantom are simulated. Motion-compensated reconstructions with varying accuracy of the applied motion field are carried out for a late diastolic heart phase and compared to the reconstruction obtained with the standard FDK-method from projections of the corresponding motion-free model in the same heart phase. Furthermore, gated reconstructions are calculated by weighting the projections according to their cardiac phase without using a motion vector field. Different gating window widths are applied, and the reconstructions are compared. Using the correct motion field with the motion-compensated reconstruction, the image quality of the standard reconstruction from the corresponding motion-free coronary model can almost be recovered. The reconstructed image quality stays acceptable if the accuracy of the motion field sampling points is better than 1 mm. The gated reconstructions with a window width of 15%-20% of the cardiac cycle lead to superior results compared to nearest neighbor gating, especially for histogram based visualization and analysis. The motion-compensated reconstructions provide sharp images of the coronaries far surpassing the image quality of gated reconstructions

Projection-based motion compensation for gated coronary artery reconstruction from rotational x-ray angiograms

Three-dimensional reconstruction of coronary arteries can be performed during x-ray-guided interventions by gated reconstruction from a rotational coronary angiography sequence. Due to imperfect gating and cardiac or breathing motion, the hearts motion state might not be the same in all projections used for the reconstruction of one cardiac phase. The motion state inconsistency causes motion artefacts and degrades the reconstruction quality. These effects can be reduced by a projection-based 2D motion compensation method. Using maximum-intensity forward projections of an initial uncompensated reconstruction as reference, the projection data are transformed elastically to improve the consistency with respect to the hearts motion state. A fast iterative closest-point algorithm working on vessel centrelines is employed for estimating the optimum transformation. Motion compensation is carried out prior to and independently from a final reconstruction. The motion compensation improves the accuracy of reconstructed vessel radii and the image contrast in a software phantom study. Reconstructions of human clinical cases are presented, in which the motion compensation substantially reduces motion blur and improves contrast and visibility of the coronary arteries.

Evaluation of Iterative Sparse Object Reconstruction From Few Projections for 3-D Rotational Coronary Angiography

A 3-D reconstruction of the coronary arteries offers great advantages in the diagnosis and treatment of cardiovascular disease, compared to 2-D X-ray angiograms. Besides improved roadmapping, quantitative vessel analysis is possible. Due to the hearts motion, rotational coronary angiography typically provides only 5-10 projections for the reconstruction of each cardiac phase, which leads to a strongly undersampled reconstruction problem. Such an ill-posed problem can be approached with regularized iterative methods. The coronary arteries cover only a small fraction of the reconstruction volume. Therefore, the minimization of the \mbi L 1 norm of the reconstructed image, favoring spatially sparse images, is a suitable regularization. Additional problems are overlaid background structures and projection truncation, which can be alleviated by background reduction using a morphological top-hat filter. This paper quantitatively evaluates image reconstruction based on these ideas on software phantom data, in terms of reconstructed absorption coefficients and vessel radii. Results for different algorithms and different input data sets are compared. First results for electrocardiogram-gated reconstruction from clinical catheter-based rotational X-ray coronary angiography are presented. Excellent 3-D image quality can be achieved.

Automatic generation of 3D coronary artery centerlines using rotational X-ray angiography

A fully automated 3D centerline modeling algorithm for coronary arteries is presented. It utilizes a subset of standard rotational X-ray angiography projections that correspond to one single cardiac phase. The algorithm is based on a fast marching approach, which selects voxels in 3D space that belong to the vascular structure and introduces a hierarchical order. The local 3D propagation speed is determined by a combination of corresponding 2D projections filtered with a vessel enhancing kernel. The best achievable accuracy of the algorithm is evaluated on simulated projections of a virtual heart phantom, showing that it is capable of extracting coronary centerlines with an accuracy that is mainly limited by projection and volume quantization (0.25 mm). The algorithm is reasonably insensitive to residual motion, which means that it is able to cope with inconsistencies within the projection data set caused by limited gating accuracy and respiration. Its accuracy on clinical data is evaluated based on expert ratings of extracted models of 17 consecutive clinical cases (10 LCA, 7 RCA). A success rate of 93.5% (i.e. with no or slight deviations) is achieved compared to 58.8% success rate of semi-automatically extracted models.

Directional View Interpolation for Compensation of Sparse Angular Sampling in Cone-Beam CT

In flat detector cone-beam computed tomography and related applications, sparse angular sampling frequently leads to characteristic streak artifacts. To overcome this problem, it has been suggested to generate additional views by means of interpolation. The practicality of this approach is investigated in combination with a dedicated method for angular interpolation of 3-D sinogram data. For this purpose, a novel dedicated shape-driven directional interpolation algorithm based on a structure tensor approach is developed. Quantitative evaluation shows that this method clearly outperforms conventional scene-based interpolation schemes. Furthermore, the image quality trade-offs associated with the use of interpolated intermediate views are systematically evaluated for simulated and clinical cone-beam computed tomography data sets of the human head. It is found that utilization of directionally interpolated views significantly reduces streak artifacts and noise, at the expense of small introduced image blur.

Motion compensated iterative reconstruction of a region of interest in cardiac cone-beam CT

A method for motion compensated iterative CT reconstruction of a cardiac region-of-interest is presented. The algorithm is an ordered subset maximum likelihood approach with spherically symmetric basis functions, and it uses an ECG for gating. Since the straightforward application of iterative methods to CT data has the drawback that a field-of-view has to be reconstructed, which covers the complete volume contributing to the absorption, region-of-interest reconstruction is applied here. Despite gating, residual object motion within the reconstructed gating window leads to motion blurring in the reconstructed image. To limit this effect, motion compensation is applied. Hereto, a gated 4D reconstruction at multiple phases is generated for the region-of-interest, and a limited set of vascular landmarks are manually annotated throughout the cardiac phases. A dense motion vector field is obtained from these landmarks by scattered data interpolation. The method is applied to two clinical data sets at strongest motion phases. Comparing the method to standard gated iterative reconstruction results shows that motion compensation strongly improved reconstruction quality.

Automatic generation of time resolved motion vector fields of coronary arteries and 4D surface extraction using rotational x-ray angiography

Rotational coronary angiography provides a multitude of x-ray projections of the contrast agent enhanced coronary arteries along a given trajectory with parallel ECG recording. These data can be used to derive motion information of the coronary arteries including vessel displacement and pulsation. In this paper, a fully automated algorithm to generate 4D motion vector fields for coronary arteries from multi-phase 3D centerline data is presented. The algorithm computes similarity measures of centerline segments at different cardiac phases and defines corresponding centerline segments as those with highest similarity. In order to achieve an excellent matching accuracy, an increasing number of bifurcations is included as reference points in an iterative manner. Based on the motion data, time-dependent vessel surface extraction is performed on the projections without the need of prior reconstruction. The algorithm accuracy is evaluated quantitatively on phantom data. The magnitude of longitudinal errors (parallel to the centerline) reaches approx. 0.50 mm and is thus more than twice as large as the transversal 3D extraction errors of the underlying multi-phase 3D centerline data. It is shown that the algorithm can extract asymmetric stenoses accurately. The feasibility on clinical data is demonstrated on five different cases. The ability of the algorithm to extract time-dependent surface data, e.g. for quantification of pulsating stenosis is demonstrated.

Directional interpolation of sparsely sampled cone-beam CT sinogram data

To compensate for sparse angular sampling in cone-beam computed tomography causing characteristic streak artifacts, we propose to increase the number of projected views by means of nonlinear directional interpolation. For this purpose, a specific method for accurate interpolation of 3D sinogram data based on a structure tensor approach has been developed. Quantitative evaluation of the interpolation error shows that our method clearly outperforms conventional interpolation schemes. Using a set of simulated cone-beam CT projection data, it is demonstrated that inclusion of interpolated projections into the reconstruction process significantly reduces streak artifacts and noise while preserving spatial resolution to a high degree.

Cardiac C-arm computed tomography using a 3D + time ROI reconstruction method with spatial and temporal regularization

PURPOSE Reconstruction of the beating heart in 3D + time in the catheter laboratory using only the available C-arm system would improve diagnosis, guidance, device sizing, and outcome control for intracardiac interventions, e.g., electrophysiology, valvular disease treatment, structural or congenital heart disease. To obtain such a reconstruction, the patients electrocardiogram (ECG) must be recorded during the acquisition and used in the reconstruction. In this paper, the authors present a 4D reconstruction method aiming to reconstruct the heart from a single sweep 10 s acquisition. METHODS The authors introduce the 4D RecOnstructiOn using Spatial and TEmporal Regularization (short 4D ROOSTER) method, which reconstructs all cardiac phases at once, as a 3D + time volume. The algorithm alternates between a reconstruction step based on conjugate gradient and four regularization steps: enforcing positivity, averaging along time outside a motion mask that contains the heart and vessels, 3D spatial total variation minimization, and 1D temporal total variation minimization. RESULTS 4D ROOSTER recovers the different temporal representations of a moving Shepp and Logan phantom, and outperforms both ECG-gated simultaneous algebraic reconstruction technique and prior image constrained compressed sensing on a clinical case. It generates 3D + time reconstructions with sharp edges which can be used, for example, to estimate the patients left ventricular ejection fraction. CONCLUSIONS 4D ROOSTER can be applied for human cardiac C-arm CT, and potentially in other dynamic tomography areas. It can easily be adapted to other problems as regularization is decoupled from projection and back projection.

High‐quality 3‐D coronary artery imaging on an interventional C‐arm x‐ray system

PURPOSE Three-dimensional (3-D) reconstruction of the coronary arteries during a cardiac catheter-based intervention can be performed from a C-arm based rotational x-ray angiography sequence. It can support the diagnosis of coronary artery disease, treatment planning, and intervention guidance. 3-D reconstruction also enables quantitative vessel analysis, including vessel dynamics from a time-series of reconstructions. METHODS The strong angular undersampling and motion effects present in gated cardiac reconstruction necessitate the development of special reconstruction methods. This contribution presents a fully automatic method for creating high-quality coronary artery reconstructions. It employs a sparseness-prior based iterative reconstruction technique in combination with projection-based motion compensation. RESULTS The method is tested on a dynamic software phantom, assessing reconstruction accuracy with respect to vessel radii and attenuation coefficients. Reconstructions from clinical cases are presented, displaying high contrast, sharpness, and level of detail. CONCLUSIONS The presented method enables high-quality 3-D coronary artery imaging on an interventional C-arm system.