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

Abstract

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.

Total Variation Regularization Method for 3D Rotational Coronary Angiography

“…The algorithm can be described as -Step 1: Do N ART iteration steps of the standard ART. -Step 2: Do N T V iteration steps of the gradient descent update for minimizing min x µ||x|| T V + ||x − v|| 2 2 , (v is calculated from step 1) -Step 3: Repeat step1 and step 2 until ||x (t) − x (t+1) || 2 2 is less than a certain value or the maximum iteration number is reached.…”

“…One way of tackling this problem is to first estimate the motion of the arteries and then perform a motion-compensated reconstruction. But it is still a challenging problem to get an accurate motion model, especially for the non-periodic case [2].…”

Automatic Extraction of 3D Dynamic Left Ventricle Model from 2D Rotational Angiocardiogram

“…Using the estimated 3D cardiac motion, we perform motion-compensated reconstruction [11]. As shown in Fig.…”

Dynamic Cone Beam Reconstruction Using a New Level Set Formulation

“…Temporally distant but spatially consistent projections (yielding a wider baseline) are used to reconstruct 3D points and track them over time. Using traditional computed tomography solutions (like filtered back projection [4] or algebraic reconstruction [5,6]) Prümmer et al [7] and Schäfer et al [8] perform phase-wise tomographic reconstructions. These phase-wise reconstructions can then be fused if the motion between cardiac phases is somehow known.…”

“…These phase-wise reconstructions can then be fused if the motion between cardiac phases is somehow known. [8] focuses on the motion-compensated FDK-reconstruction algorithm assuming a known motion field whereas [7] also proposes to do multiple sweeps for acquiring enough projection data.…”