ArticleOptics express2023
Neu(t)ralMC: energy-efficient open source Monte Carlo algorithm for assessing photon transport in turbid media.
Article in Optics express, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- Anatomy-resolved digital twin framework for personalized light dosimetry in lung therapies.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Using large language models for enhancing accessibility for Monte Carlo photon transport simulations and beyond.bioRxiv : the preprint server for biology · 2026Article
- Scaling method for efficient Monte Carlo simulation of fluorescence spectra from multi-layered turbid media with oblique illumination and collection geometry.Biomedical optics express · 2025Article
- Twists through turbidity: propagation of light carrying orbital angular momentum through a complex scattering medium.Scientific reports · 2024Article
- Photodynamic treatment of malignant melanoma with structured light:Biomedical optics express · 2024Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Light propagation in turbid mediums such as atmosphere, fluids, and biological tissues is a challenging problem which necessitates accurate simulation techniques to account for the effects of multiple scattering. The Monte Carlo method has long established itself as a gold standard and is widely adopted for simulating light transport, however, its computationally intensive nature often requires significant processing power and energy consumption. In this paper a novel, open source Monte Carlo algorithm is introduced which is specifically designed for use with energy-efficient processors, effectively addressing those challenges, while maintaining the accuracy/compatibility and outperforming existing solutions. The proposed implementation optimizes photon transport simulations by exploiting the unique capabilities of Apple's low-power, high-performance M-family of chips. The developed method has been implemented in an open-source software package, enabling seamless adaptation of developed algorithms for specific applications. The accuracy and performance are validated using comprehensive comparison with existing solvers commonly used for biomedical imaging. The results demonstrate that the new algorithm achieves comparable accuracy levels to those of existing techniques while significantly reducing computational time and energy consumption.
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.