Presentation
5 March 2021 Reducing boundary voxelization errors of 3-D monte carlo photon simulation
Shijie Yan, Qianqian Fang
Author Affiliations +
Abstract
The voxel-based Monte Carlo method (VMC) offers efficiency in modeling light transport in complex bio-tissues, but is known to produce erroneous results due to its terraced boundaries. We present a significantly improved VMC by incorporating mesh-based boundary information in a hybrid modeling approach. A fast preprocessing step first extracts surface meshes from an arbitrary voxelated domain using the marching-cubes algorithm. An extended voxel format is developed to encode oblique surface information while keeping the data structure efficient for parallel processing. This enables modeling of subvoxel boundaries, resulting in significantly improved accuracy in benchmarks, including an MRI human brain atlas.
Conference Presentation
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shijie Yan and Qianqian Fang "Reducing boundary voxelization errors of 3-D monte carlo photon simulation", Proc. SPIE 11634, Multimodal Biomedical Imaging XVI, 116340A (5 March 2021); https://doi.org/10.1117/12.2583185
Advertisement
Advertisement
KEYWORDS
Monte Carlo methods

Image segmentation

Tissues

Photon transport

3D modeling

Biomedical optics

Computer simulations

Back to Top