Massively parallel simulator of optical coherence tomography of inhomogeneous turbid media

Siavash Malektaji; Ivan T Lima Jr; Mauricio R Escobar I; Sherif S Sherif

doi:10.1016/j.cmpb.2017.08.001

Massively parallel simulator of optical coherence tomography of inhomogeneous turbid media

Comput Methods Programs Biomed. 2017 Oct:150:97-105. doi: 10.1016/j.cmpb.2017.08.001. Epub 2017 Aug 8.

Authors

Siavash Malektaji¹, Ivan T Lima Jr², Mauricio R Escobar I¹, Sherif S Sherif³

Affiliations

¹ University of Manitoba, Department of Electrical and Computer Engineering, 75A Chancellor's Circle, Winnipeg, Manitoba R3T 5V6, Canada.
² North Dakota State University, Department of Electrical and Computer Engineering, 1411 Centennial Boulevard, Fargo, ND 58108-6050, USA.
³ University of Manitoba, Department of Electrical and Computer Engineering, 75A Chancellor's Circle, Winnipeg, Manitoba R3T 5V6, Canada. Electronic address: Sherif.Sherif@umanitoba.ca.

PMID: 28859833
DOI: 10.1016/j.cmpb.2017.08.001

Abstract

Background and objective: An accurate and practical simulator for Optical Coherence Tomography (OCT) could be an important tool to study the underlying physical phenomena in OCT such as multiple light scattering. Recently, many researchers have investigated simulation of OCT of turbid media, e.g., tissue, using Monte Carlo methods. The main drawback of these earlier simulators is the long computational time required to produce accurate results. We developed a massively parallel simulator of OCT of inhomogeneous turbid media that obtains both Class I diffusive reflectivity, due to ballistic and quasi-ballistic scattered photons, and Class II diffusive reflectivity due to multiply scattered photons.

Methods: This Monte Carlo-based simulator is implemented on graphic processing units (GPUs), using the Compute Unified Device Architecture (CUDA) platform and programming model, to exploit the parallel nature of propagation of photons in tissue. It models an arbitrary shaped sample medium as a tetrahedron-based mesh and uses an advanced importance sampling scheme.

Results: This new simulator speeds up simulations of OCT of inhomogeneous turbid media by about two orders of magnitude. To demonstrate this result, we have compared the computation times of our new parallel simulator and its serial counterpart using two samples of inhomogeneous turbid media. We have shown that our parallel implementation reduced simulation time of OCT of the first sample medium from 407 min to 92 min by using a single GPU card, to 12 min by using 8 GPU cards and to 7 min by using 16 GPU cards. For the second sample medium, the OCT simulation time was reduced from 209 h to 35.6 h by using a single GPU card, and to 4.65 h by using 8 GPU cards, and to only 2 h by using 16 GPU cards. Therefore our new parallel simulator is considerably more practical to use than its central processing unit (CPU)-based counterpart.

Conclusions: Our new parallel OCT simulator could be a practical tool to study the different physical phenomena underlying OCT, or to design OCT systems with improved performance.

Keywords: Light propagation in tissue; Optical coherence tomography; Parallel processing.

MeSH terms

Computer Graphics
Computer Simulation
Models, Biological
Monte Carlo Method
Nephelometry and Turbidimetry*
Photons
Tomography, Optical Coherence*