Abstract
BackgroundFor cone-beam computed tomography (CBCT), which has been playing an important role in clinical applications, iterative reconstruction algorithms are able to provide advantageous image qualities over the classical FDK. However, the computational speed of iterative reconstruction is a notable issue for CBCT, of which the forward projection calculation is one of the most time-consuming components.Method and resultsIn this study, the cone-beam forward projection problem using the voxel-driven model is analysed, and a GPU-based acceleration method for CBCT forward projection is proposed with the method rationale and implementation workflow detailed as well. For method validation and evaluation, computational simulations are performed, and the calculation times of different methods are collected. Compared with the benchmark CPU processing time, the proposed method performs effectively in handling the inter-thread interference problem, and an acceleration ratio as high as more than 100 is achieved compared to a single-threaded CPU implementation.ConclusionThe voxel-driven forward projection calculation for CBCT is highly paralleled by the proposed method, and we believe it will serve as a critical module to develop iterative reconstruction and correction methods for CBCT imaging.
Highlights
For cone-beam computed tomography (CBCT), which has been playing an important role in clinical applications, iterative reconstruction algorithms are able to provide advantageous image qualities over the classical FDK
Due to the insufficient data conditioning caused by the circular trajectory, the images of CBCT are susceptible to artefacts, noise and the scatter effect [6]
This paper is organized as follows: the voxel-driven projection algorithm and the inter-thread interference problem are first investigated in “Voxel-driven model and inter-thread interference study” section; based on the analysis, the proposed graphic processing unit (GPU) acceleration method is detailed in “Combating strategy by optimizing thread-grid allocation” section, with a brief workflow in “Implementation outline” section; as method validation, computational simulations are performed with results given in “Experiment and results” section; some issues are discussed and major conclusions are drawn in “Discussion and conclusion” section
Summary
Cone-beam computed tomography (CBCT) has been advanced to serve as a widely available and commonly used imaging modality in clinical applications, such as dental diagnostics [1], image-guided radiotherapy [2], intraoperative navigation [3], and implant planning [4], and has broadened its usage in new settings, including breast cancer screening and endodontics [5]. Several compute models have been proposed as matched forward/back projector pairs, including distance-driven [15] and separable-footprint approaches [16], and some have been successively GPU-accelerated with specific strategies [17,18,19]. Among these models, the voxel-driven method is extensively used to perform CBCT forward and back projections for its low complexity. This paper is organized as follows: the voxel-driven projection algorithm and the inter-thread interference problem are first investigated in “Voxel-driven model and inter-thread interference study” section; based on the analysis, the proposed GPU acceleration method is detailed in “Combating strategy by optimizing thread-grid allocation” section, with a brief workflow in “Implementation outline” section; as method validation, computational simulations are performed with results given in “Experiment and results” section; some issues are discussed and major conclusions are drawn in “Discussion and conclusion” section
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