Int J Comput Assist Radiol Surg - Accelerating simultaneous algebraic reconstruction technique with motion compensation using CUDA-enabled GPU.

Tópicos

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Resumo

RPOSE: To accelerate the simultaneous algebraic reconstruction technique (SART) with motion compensation for speedy and quality computed tomography reconstruction by exploiting CUDA-enabled GPU.METHODS: Two core techniques are proposed to fit SART into the CUDA architecture: (1) a ray-driven projection along with hardware trilinear interpolation, and (2) a voxel-driven back-projection that can avoid redundant computation by combining CUDA shared memory. We utilize the independence of each ray and voxel on both techniques to design CUDA kernel to represent a ray in the projection and a voxel in the back-projection respectively. Thus, significant parallelization and performance boost can be achieved. For motion compensation, we rectify each ray's direction during the projection and back-projection stages based on a known motion vector field.RESULTS: Extensive experiments demonstrate the proposed techniques can provide faster reconstruction without compromising image quality. The process rate is nearly 100 projections s (-1), and it is about 150 times faster than a CPU-based SART. The reconstructed image is compared against ground truth visually and quantitatively by peak signal-to-noise ratio (PSNR) and line profiles. We further evaluate the reconstruction quality using quantitative metrics such as signal-to-noise ratio (SNR) and mean-square-error (MSE). All these reveal that satisfactory results are achieved. The effects of major parameters such as ray sampling interval and relaxation parameter are also investigated by a series of experiments. A simulated dataset is used for testing the effectiveness of our motion compensation technique. The results demonstrate our reconstructed volume can eliminate undesirable artifacts like blurring.CONCLUSION: Our proposed method has potential to realize instantaneous presentation of 3D CT volume to physicians once the projection data are acquired.

Resumo Limpo

rpose acceler simultan algebra reconstruct techniqu sart motion compens speedi qualiti comput tomographi reconstruct exploit cudaen gpumethod two core techniqu propos fit sart cuda architectur raydriven project along hardwar trilinear interpol voxeldriven backproject can avoid redund comput combin cuda share memori util independ ray voxel techniqu design cuda kernel repres ray project voxel backproject respect thus signific parallel perform boost can achiev motion compens rectifi ray direct project backproject stage base known motion vector fieldresult extens experi demonstr propos techniqu can provid faster reconstruct without compromis imag qualiti process rate near project s time faster cpubas sart reconstruct imag compar ground truth visual quantit peak signaltonois ratio psnr line profil evalu reconstruct qualiti use quantit metric signaltonois ratio snr meansquareerror mse reveal satisfactori result achiev effect major paramet ray sampl interv relax paramet also investig seri experi simul dataset use test effect motion compens techniqu result demonstr reconstruct volum can elimin undesir artifact like blurringconclus propos method potenti realiz instantan present d ct volum physician project data acquir

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