Abstract:

As the most accurate model for simulating light propagation in
heterogeneous tissues, Monte Carlo (MC) method has been widely used in
the field of optical molecular imaging. However, MC method is timeconsuming
due to the calculations of a large number of photons propagation
in tissues. The structural complexity of the heterogeneous tissues further
increases the computational time. In this paper we present a parallel
implementation for MC simulation of light propagation in heterogeneous
tissues whose surfaces are constructed by different number of triangle
meshes. On the basis of graphics processing units (GPU), the code is
implemented with compute unified device architecture (CUDA) platform
and optimized to reduce the access latency as much as possible by making
full use of the constant memory and texture memory on GPU. We test the
implementation in the homogeneous and heterogeneous mouse models with
a NVIDIA GTX 260 card and a 2.40GHz Intel Xeon CPU. The
experimental results demonstrate the feasibility and efficiency of the
parallel MC simulation on GPU.