Result: NIRFASTerFF: an accessible, cross-platform Python package for fast photon modeling.

Title:
NIRFASTerFF: an accessible, cross-platform Python package for fast photon modeling.
Authors:
Cao J; University of Birmingham, School of Computer Science, Birmingham, United Kingdom., Montero-Hernandez S; University of Birmingham, School of Computer Science, Birmingham, United Kingdom., Mesquita RC; University of Birmingham, School of Computer Science, Birmingham, United Kingdom., Eggebrecht AT; Washington University School of Medicine, Mallinckrodt Institute of Radiology, St. Louis, Missouri, United States., Dehghani H; University of Birmingham, School of Computer Science, Birmingham, United Kingdom.
Source:
Journal of biomedical optics [J Biomed Opt] 2025 Nov; Vol. 30 (11), pp. 115001. Date of Electronic Publication: 2025 Nov 03.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Published by SPIE--the International Society for Optical Engineering in cooperation with International Biomedical Optics Society Country of Publication: United States NLM ID: 9605853 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1560-2281 (Electronic) Linking ISSN: 10833668 NLM ISO Abbreviation: J Biomed Opt Subsets: MEDLINE
Imprint Name(s):
Original Publication: Bellingham, WA : Published by SPIE--the International Society for Optical Engineering in cooperation with International Biomedical Optics Society, c1996-
MeSH Terms:
Photons* , Image Processing, Computer-Assisted*/methods , Software* , Optical Imaging*/methods, Monte Carlo Method ; Algorithms ; Finite Element Analysis ; Computer Simulation ; Phantoms, Imaging
References:
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Contributed Indexing:
Keywords: algorithm; diffuse optics; finite element method; mathematical modeling; parallel computing; toolbox
Entry Date(s):
Date Created: 20251107 Date Completed: 20251107 Latest Revision: 20251109
Update Code:
20251109
PubMed Central ID:
PMC12587457
DOI:
10.1117/1.JBO.30.11.115001
PMID:
41199898
Database:
MEDLINE

Further Information

Significance: Accurate and efficient photon modeling plays an essential role in the rapidly developing field of diffuse optical imaging, whereby the use of model-based analysis and image reconstruction can provide both educational and research benefits.
Aim: NIRFASTerFF is a cross-platform (Linux, macOS, and Windows) Python package for finite element method (FEM)-based light propagation modeling, supporting continuous-wave, frequency-domain, and time-resolved data for both exogenous and endogenous optical imaging applications. It also enables modeling of the autocorrelation function ( INLINEMATH ) for diffuse correlation spectroscopy. Validation is performed through comparison with the original NIRFAST and gold-standard Monte Carlo simulations.
Approach: NIRFASTerFF incorporates highly parallelized FEM solvers for efficient computation on both CPU and GPU, leveraging OpenMP and CUDA acceleration. To support image reconstruction tasks, voxel-based interpolation of the optical fluence is implemented, providing a flexible and accurate representation of the forward solution suitable for inverse problem formulations.
Results: Compared with its predecessor, NIRFASTer, the optimized algorithms provide a performance boost of 25% to 45% on GPU and up to 20% on CPU, and the results show good agreement with both Monte Carlo and analytical solutions.
Conclusion: The NIRFASTerFF package provides a fast and license-free tool for photon modeling and can further streamline Python-based data processing in diffuse optical imaging, benefiting the biophotonics community.
(© 2025 The Authors.)