• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

通过“光子共享”加速基于结构光的漫射光学成像的蒙特卡罗建模。

Accelerating Monte Carlo modeling of structured-light-based diffuse optical imaging via "photon sharing".

出版信息

Opt Lett. 2020 May 15;45(10):2842-2845. doi: 10.1364/OL.390618.

DOI:10.1364/OL.390618
PMID:32412482
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7482422/
Abstract

The increasing use of spatially modulated imaging and single-pixel detection techniques demands computationally efficient methods for light transport modeling. Herein, we report an easy-to-implement yet significantly more efficient Monte Carlo (MC) method for simultaneously simulating spatially modulated illumination and detection patterns accurately in 3D complex domains. We have implemented this accelerated algorithm, named "photon sharing," in our open-source MC simulators, reporting 13.6× and 5.5× speedups in mesh- and voxel-based MC benchmarks, respectively. In addition, the proposed algorithm is readily used to accelerate the solving of inverse problems in spatially modulated imaging systems by building Jacobians of all illumination-detection pattern pairs concurrently, resulting in a 12.4-fold speed improvement.

摘要

空间调制成像和单像素检测技术的应用日益广泛,这就需要计算效率高的方法来进行光传输建模。在此,我们报告了一种易于实现但效率显著提高的蒙特卡罗(MC)方法,可在 3D 复杂域中同时准确模拟空间调制照明和检测模式。我们已经在我们的开源 MC 模拟器中实现了这种加速算法,名为“光子共享”,在基于网格和体素的 MC 基准测试中分别实现了 13.6 倍和 5.5 倍的加速。此外,通过同时构建所有照明-检测模式对的雅可比矩阵,该算法可用于加速空间调制成像系统中的逆问题求解,从而将速度提高 12.4 倍。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/080d/7482422/fddc285186a2/nihms-1624643-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/080d/7482422/444e2b843698/nihms-1624643-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/080d/7482422/fddc285186a2/nihms-1624643-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/080d/7482422/444e2b843698/nihms-1624643-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/080d/7482422/fddc285186a2/nihms-1624643-f0002.jpg

相似文献

1
Accelerating Monte Carlo modeling of structured-light-based diffuse optical imaging via "photon sharing".通过“光子共享”加速基于结构光的漫射光学成像的蒙特卡罗建模。
Opt Lett. 2020 May 15;45(10):2842-2845. doi: 10.1364/OL.390618.
2
Hybrid mesh and voxel based Monte Carlo algorithm for accurate and efficient photon transport modeling in complex bio-tissues.基于混合网格和体素的蒙特卡罗算法,用于复杂生物组织中精确高效的光子传输建模。
Biomed Opt Express. 2020 Oct 8;11(11):6262-6270. doi: 10.1364/BOE.409468. eCollection 2020 Nov 1.
3
Direct approach to compute Jacobians for diffuse optical tomography using perturbation Monte Carlo-based photon "replay".基于微扰蒙特卡罗光子“重放”法直接计算漫射光学层析成像的雅可比矩阵
Biomed Opt Express. 2018 Sep 4;9(10):4588-4603. doi: 10.1364/BOE.9.004588. eCollection 2018 Oct 1.
4
Graphics-processing-unit-accelerated Monte Carlo simulation of polarized light in complex three-dimensional media.基于图形处理单元的复杂三维介质中偏振光的蒙特卡罗模拟。
J Biomed Opt. 2022 May;27(8). doi: 10.1117/1.JBO.27.8.083015.
5
Generalized mesh-based Monte Carlo for wide-field illumination and detection via mesh retessellation.基于广义网格的蒙特卡罗方法,用于通过网格重新细分实现宽场照明和检测。
Biomed Opt Express. 2015 Dec 18;7(1):171-84. doi: 10.1364/BOE.7.000171. eCollection 2016 Jan 1.
6
Monte Carlo-based data generation for efficient deep learning reconstruction of macroscopic diffuse optical tomography and topography applications.基于蒙特卡罗的数据生成,用于高效的宏观漫射光学断层扫描和层析成像应用的深度学习重建。
J Biomed Opt. 2022 Apr;27(8). doi: 10.1117/1.JBO.27.8.083016.
7
Graphics processing unit-accelerated mesh-based Monte Carlo photon transport simulations.基于图形处理单元加速的网格蒙特卡罗光子传输模拟。
J Biomed Opt. 2019 Nov;24(11):1-6. doi: 10.1117/1.JBO.24.11.115002.
8
Dual-grid mesh-based Monte Carlo algorithm for efficient photon transport simulations in complex three-dimensional media.基于双重网格的蒙特卡罗算法在复杂三维介质中高效光子传输模拟。
J Biomed Opt. 2019 Feb;24(2):1-4. doi: 10.1117/1.JBO.24.2.020503.
9
Light transport modeling in highly complex tissues using the implicit mesh-based Monte Carlo algorithm.使用基于隐式网格的蒙特卡罗算法对高度复杂组织中的光传输进行建模。
Biomed Opt Express. 2020 Dec 8;12(1):147-161. doi: 10.1364/BOE.411898. eCollection 2021 Jan 1.
10
Graphics processing units-accelerated adaptive nonlocal means filter for denoising three-dimensional Monte Carlo photon transport simulations.图形处理单元加速的自适应非局部均值滤波器在三维蒙特卡罗光子输运模拟中的去噪应用。
J Biomed Opt. 2018 Nov;23(12):1-9. doi: 10.1117/1.JBO.23.12.121618.

引用本文的文献

1
Revisiting the Rytov approximation in diffuse optics and its applications for the inverse and forward problems.重新审视扩散光学中的 Rytov 近似及其在正反问题中的应用。
Sci Rep. 2024 Dec 28;14(1):31266. doi: 10.1038/s41598-024-82682-3.
2
Challenges and advances in optical 3D mesoscale imaging.光学 3D 介观成像的挑战与进展。
J Microsc. 2022 Jun;286(3):201-219. doi: 10.1111/jmi.13109. Epub 2022 May 5.
3
High-resolution three-dimensional blood flow tomography in the subdiffuse regime using laser speckle contrast imaging.

本文引用的文献

1
Graphics processing unit-accelerated mesh-based Monte Carlo photon transport simulations.基于图形处理单元加速的网格蒙特卡罗光子传输模拟。
J Biomed Opt. 2019 Nov;24(11):1-6. doi: 10.1117/1.JBO.24.11.115002.
2
Spatial frequency domain imaging in 2019: principles, applications, and perspectives.空间频域成像 2019:原理、应用及展望。
J Biomed Opt. 2019 Jun;24(7):1-18. doi: 10.1117/1.JBO.24.7.071613.
3
Direct approach to compute Jacobians for diffuse optical tomography using perturbation Monte Carlo-based photon "replay".
利用激光散斑对比成像技术在亚扩散区域进行高分辨率三维血流层析成像。
J Biomed Opt. 2022 Mar;27(8). doi: 10.1117/1.JBO.27.8.083011.
4
Light transport modeling in highly complex tissues using the implicit mesh-based Monte Carlo algorithm.使用基于隐式网格的蒙特卡罗算法对高度复杂组织中的光传输进行建模。
Biomed Opt Express. 2020 Dec 8;12(1):147-161. doi: 10.1364/BOE.411898. eCollection 2021 Jan 1.
基于微扰蒙特卡罗光子“重放”法直接计算漫射光学层析成像的雅可比矩阵
Biomed Opt Express. 2018 Sep 4;9(10):4588-4603. doi: 10.1364/BOE.9.004588. eCollection 2018 Oct 1.
4
Review of structured light in diffuse optical imaging.结构光漫射光学成像综述。
J Biomed Opt. 2018 Sep;24(7):1-20. doi: 10.1117/1.JBO.24.7.071602.
5
Assessing patterns for compressive fluorescence lifetime imaging.评估压缩荧光寿命成像的模式。
Opt Lett. 2018 Sep 15;43(18):4370-4373. doi: 10.1364/OL.43.004370.
6
Overview of diffuse optical tomography and its clinical applications.漫射光学断层成像及其临床应用概述。
J Biomed Opt. 2016 Sep;21(9):091312. doi: 10.1117/1.JBO.21.9.091312.
7
Generalized mesh-based Monte Carlo for wide-field illumination and detection via mesh retessellation.基于广义网格的蒙特卡罗方法,用于通过网格重新细分实现宽场照明和检测。
Biomed Opt Express. 2015 Dec 18;7(1):171-84. doi: 10.1364/BOE.7.000171. eCollection 2016 Jan 1.
8
Mesoscopic Fluorescence Molecular Tomography for Evaluating Engineered Tissues.用于评估工程组织的介观荧光分子断层成像
Ann Biomed Eng. 2016 Mar;44(3):667-79. doi: 10.1007/s10439-015-1511-4. Epub 2015 Dec 8.
9
Hyperspectral time-resolved wide-field fluorescence molecular tomography based on structured light and single-pixel detection.基于结构光和单像素检测的高光谱时间分辨宽场荧光分子断层成像
Opt Lett. 2015 Feb 1;40(3):431-4. doi: 10.1364/OL.40.000431.
10
Accelerating mesh-based Monte Carlo method on modern CPU architectures.在现代CPU架构上加速基于网格的蒙特卡罗方法。
Biomed Opt Express. 2012 Dec 1;3(12):3223-30. doi: 10.1364/BOE.3.003223. Epub 2012 Nov 12.