Accelerating frequency-domain diffuse optical tomographic image reconstruction using graphics processing units

Jaya Prakash; Venkittarayan Chandrasekharan; Vishwajith Upendra; Phaneedra K. Yalavarthy

doi:10.1117/1.3506216

1 November 2010 Accelerating frequency-domain diffuse optical tomographic image reconstruction using graphics processing units

Jaya Prakash, Venkittarayan Chandrasekharan, Vishwajith Upendra, Phaneedra K. Yalavarthy

Author Affiliations +

Journal of Biomedical Optics, Vol. 15, Issue 6, 066009 (November 2010). https://doi.org/10.1117/1.3506216

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.

©(2010) Society of Photo-Optical Instrumentation Engineers (SPIE)

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Jaya Prakash, Venkittarayan Chandrasekharan, Vishwajith Upendra, and Phaneedra K. Yalavarthy "Accelerating frequency-domain diffuse optical tomographic image reconstruction using graphics processing units," Journal of Biomedical Optics 15(6), 066009 (1 November 2010). https://doi.org/10.1117/1.3506216

Published: 1 November 2010

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KEYWORDS

Image restoration

Tomography

Data modeling

Computing systems

Optical properties

Matrices

Reconstruction algorithms

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