GPU-Based 3D Cone-Beam CT Image Reconstruction for Large Data Volume
نویسندگان
چکیده
منابع مشابه
GPU-Based 3D Cone-Beam CT Image Reconstruction for Large Data Volume
Currently, 3D cone-beam CT image reconstruction speed is still a severe limitation for clinical application. The computational power of modern graphics processing units (GPUs) has been harnessed to provide impressive acceleration of 3D volume image reconstruction. For extra large data volume exceeding the physical graphic memory of GPU, a straightforward compromise is to divide data volume into...
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Three dimension Computed Tomography (CT) reconstruction is computationally demanding. To accelerate the speed of reconstruction, Application Specific Integrated Circuit (ASIC) or Field Programmable Gate Array (FPGA) has been used, but they are expensive, inflexible and not easy to upgrade. The modern Graphics Processing Unit (GPU) with its programmable features improves this situation and becom...
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Iterative image reconstruction (IIR) with sparsity-exploiting methods, such as total variation (TV) minimization, claims potentially large reductions in sampling requirements. However, the computation complexity becomes a heavy burden, especially in 3D reconstruction situations. In order to improve the performance for iterative reconstruction, an efficient IIR algorithm for cone-beam computed t...
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PURPOSE Cone-beam CT (CBCT) plays an important role in image guided radiation therapy (IGRT). However, the large radiation dose from serial CBCT scans in most IGRT procedures raises a clinical concern, especially for pediatric patients who are essentially excluded from receiving IGRT for this reason. The goal of this work is to develop a fast GPU-based algorithm to reconstruct CBCT from undersa...
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A conventional 3rd generation Computed Tomography (CT) system with a single circular source trajectory is limited in terms of longitudinal scan coverage since extending the scan coverage beyond 40 mm results in significant cone-beam artifacts. A multiaxial CT acquisition is achieved by combining multiple sequential 3rd generation axial scans or by performing a single axial multisource CT scan w...
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ژورنال
عنوان ژورنال: International Journal of Biomedical Imaging
سال: 2009
ISSN: 1687-4188,1687-4196
DOI: 10.1155/2009/149079