Registration-Based Reconstruction of Four-Dimensional Cone Beam Computed Tomography

Abstract

We present a new method for reconstruction of 4-D cone beam computed tomography from an undersampled set of X-ray projections. The novelty of the proposed method lies in utilizing optical flow based registration to facilitate that each temporal phase is reconstructed from the full set of acquired projections. The reconstruction of each phase thus exhibits limited aliasing despite significant intra-phase undersampling. The method is fully self-contained. Initially an approximate 4-D volume is reconstructed and an inter-phase registration based hereon. A subsequent reconstruction pass integrates the optical flow estimation in a cost function formulation in which the X-ray projections from all temporal phases are considered for the reconstruction of each individual phase. Quantitative and qualitative evaluations were performed through reconstruction of both a numerical phantom and a clinical dataset. The obtained reconstructions are compared to the state-of-the-art alternatives of total variation regularization and prior image constrained compressed sensing. Our studies show that the proposed method is the better overall "compromise" in the depiction of both moving and stationary anatomical structures.

A hybrid reconstruction algorithm for fast and accurate 4D cone-beam CT imaging

“…In light of the availability of this prior information, 2D-3D matching-based reconstruction models have been proposed in a wide spectrum of imaging tasks, such as tomosynthesis, real-time volumetric imaging, and 3D/4D CBCT. 27,36,37,39,[43][44][45] These methods optimize a motion vector field (MVF) to deform the p-CT, such that its forward projections match the measurements. Brock et al proposed to match the forward projections by adjusting the MVF control points, so that the forward projections have minimal mismatch with the measurements.…”

“…37 Recently, a multiple-step algorithm combing PCA modeling, optical flow based registration and reconstruction was proposed. 39 It was validated with simulation studies and one patient data study and was compared with the state-of-the-art CS-based methods, such as TV (Ref. 46) and PICCS.…”

“…In this paper, we will present an alternative approach to the existing algorithms, 36,37,39 called forward-backward splitting (FBS) algorithm, to solve the 2D-3D registration-based 4D-CBCT reconstruction problem. It splits the model into two well-studied subproblems, i.e., image reconstruction and deformable image registration (DIR).…”

“…As a comparison, hours of computation time are usually observed for those CPU based 2D-3D matching algorithms. 39 Both phantom and multiple real patient data sets are used to test the efficacy of the proposed algorithm. For each case, comprehensive evaluations are conducted regarding the image quality, algorithm robustness, and computational efficiency.…”

A Novel Method of Cone Beam CT Projection Binning Based on Image Registration

“…Some of these methods are based on phase binning [2]-[4], [9]-[12] and the others use respiration models to deform either the reconstructed volume or the back-projection operation [13], [14]. The reconstructed image quality of all of these methods directly relies on the performance of respiratory signal extraction because all of these techniques require tagging raw data (e.g., radiographic projections) with a respiratory phase or state [3]-[11], [13]. …”