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• W2023648587 startingPage "066009" @default.
• W2023648587 abstract "Diffuse optical tomographic image reconstruction uses advanced numerical models that are computationally costly to be implemented in the real time. The graphics processing units (GPUs) offer desktop massive parallelization that can accelerate these computations. An open-source GPU-accelerated linear algebra library package is used to compute the most intensive matrix-matrix calculations and matrix decompositions that are used in solving the system of linear equations. These open-source functions were integrated into the existing frequency-domain diffuse optical image reconstruction algorithms to evaluate the acceleration capability of the GPUs (NVIDIA Tesla C 1060) with increasing reconstruction problem sizes. These studies indicate that single precision computations are sufficient for diffuse optical tomographic image reconstruction. The acceleration per iteration can be up to 40, using GPUs compared to traditional CPUs in case of three-dimensional reconstruction, where the reconstruction problem is more underdetermined, making the GPUs more attractive in the clinical settings. The current limitation of these GPUs in the available onboard memory (4 GB) that restricts the reconstruction of a large set of optical parameters, more than 13,377." @default.
• W2023648587 created "2016-06-24" @default.
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• W2023648587 creator A5068561041 @default.
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• W2023648587 date "2010-01-01" @default.
• W2023648587 modified "2023-10-04" @default.
• W2023648587 title "Accelerating frequency-domain diffuse optical tomographic image reconstruction using graphics processing units" @default.
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• W2023648587 doi "https://doi.org/10.1117/1.3506216" @default.
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