ArticleBiomedical optics express2019
FullMonteCUDA: a fast, flexible, and accurate GPU-accelerated Monte Carlo simulator for light propagation in turbid media.
Article in Biomedical optics express, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
What it found
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Who cites it
23 citing papers in PubMed.
- Robustness of interstitial photodynamic therapy treatment planning under power and positional uncertainties in light delivery.Scientific reports · 2026Article
- Accelerating mesh-based Monte Carlo simulations using contemporary graphics ray-tracing hardware.Journal of biomedical optics · 2026Article
- A contemporary systematic review on deterministic numerical simulations of light propagation in head tissues.Biophysical reviews · 2026Review
- Dose threshold values for endovascular photodynamic therapy (PDT) in normal pig pancreas and human pancreatic cancer.Photochemical & photobiological sciences : Official journal of the European Photochemistry Association and the European Society for Photobiology · 2025Article
- Accelerating mesh-based Monte Carlo simulations using contemporary graphics ray-tracing hardware.ArXiv · 2025Article
- Effect of skin color and other skin properties on the delivered light dose in phototherapy for neonatal hyperbilirubinemia.Biophotonics discovery · 2025Article
- Asymmetric imaging through engineered Janus particle obscurants using a Monte Carlo approach for highly asymmetric scattering media.Scientific reports · 2024Article
- Integrating clinical access limitations into iPDT treatment planning with PDT-SPACE.Biomedical optics express · 2023Article
- Efficient computation of the steady-state and time-domain solutions of the photon diffusion equation in layered turbid media.Scientific reports · 2022Article
- Meshless Monte Carlo radiation transfer method for curved geometries using signed distance functions.Journal of biomedical optics · 2022Article
- Convolutional neural network-based common-path optical coherence tomography A-scan boundary-tracking training and validation using a parallel Monte Carlo synthetic dataset.Optics express · 2022Article
- Framework for denoising Monte Carlo photon transport simulations using deep learning.Journal of biomedical optics · 2022Article
- Scalable and accessible personalized photodynamic therapy optimization with FullMonte and PDT-SPACE.Journal of biomedical optics · 2022Article
- MCDataset: a public reference dataset of Monte Carlo simulated quantities for multilayered and voxelated tissues computed by massively parallel PyXOpto Python package.Journal of biomedical optics · 2022Article
- BlenderPhotonics: an integrated open-source software environment for three-dimensional meshing and photon simulations in complex tissues.Journal of biomedical optics · 2022Article
- MCX Cloud-a modern, scalable, high-performance and in-browser Monte Carlo simulation platform with cloud computing.Journal of biomedical optics · 2022Article
- Photodynamic therapy in a pleural cavity using monte carlo simulations with 2D/3D Graphical Visualization.Global journal of cancer therapy · 2022Article
- Modeling the efficiency of UV at 254 nm for disinfecting the different layers within N95 respirators.Journal of biophotonics · 2021Article
- Review of in vivo optical molecular imaging and sensing from x-ray excitation.Journal of biomedical optics · 2021Review
- Light transport modeling in highly complex tissues using the implicit mesh-based Monte Carlo algorithm.Biomedical optics express · 2021Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Optimizing light delivery for photodynamic therapy, quantifying tissue optical properties or reconstructing 3D distributions of sources in bioluminescence imaging and absorbers in diffuse optical imaging all involve solving an inverse problem. This can require thousands of forward light propagation simulations to determine the parameters to optimize treatment, image tissue or quantify tissue optical properties, which is time-consuming and computationally expensive. Addressing this problem requires a light propagation simulator that produces results quickly given modelling parameters. In previous work, we developed FullMonteSW: currently the fastest, tetrahedral-mesh, Monte Carlo light propagation simulator written in software. Additional software optimizations showed diminishing performance improvements, so we investigated hardware acceleration methods. This work focuses on FullMonteCUDA: a GPU-accelerated version of FullMonteSW which targets NVIDIA GPUs. FullMonteCUDA has been validated across several benchmark models and, through various GPU-specific optimizations, achieves a 288-936x speedup over the single-threaded, non-vectorized version of FullMonteSW and a 4-13x speedup over the highly optimized, hand-vectorized and multi-threaded version. The increase in performance allows inverse problems to be solved more efficiently and effectively.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.