GPU-Accelerated Monte Carlo Photon Transport Simulation Platform

 描述(由申请人提供)：新的生物光子学技术继续以前所未有的速度出现，以满足迅速增长的对准确、快速、非或微创的生理学量化的临床需求。彻底了解光子和生物组织之间的复杂相互作用是这些技术的基础。在过去的5年里，我们的团队一直致力于开发计算效率高的蒙特卡罗(MC)方法来模拟复杂组织结构中的光传输。作为这项研究的结果，已经开发并发布了两个开源模拟程序包--蒙特卡罗极限(MCX)和基于网格的蒙特卡罗(MMC)。他们现在推动了世界各地许多光学实验室以及小企业的研究，全球超过240次引用、超过9000次下载和近20,000名独立网络访问者证明了这一点。在这项建议中，我们寻求进一步扩展、巩固和传播MCX和MMC，遵循NIH PA-14-156中的具体指导方针。将开发和实施基于MC的新算法，用于模拟广域照明和检测、快速层析重建和进一步加速，以满足整个社区对开发下一代光学成像技术不断增长的需求。作为经验丰富的开源开发人员和维护人员，我们接受与我们的用户社区接触的关键作用，并计划显著增强我们的软件用户体验、用户支持以及系统的拓展和培训。为了显著提高可用性和可扩展性，我们将开发基于Web的MCx/MMC以使我们的平台能够广泛访问，并开发分布式计算云以实现对大型、复杂的多模式数据集的快速处理。我们还将开发正式的培训课程和材料，以更好地教育研究人员，加强支持和反馈机制，并努力通过我们的平台创建标准化的光学成像数据交换规范。实现这些目标不仅将使MCX/MMC成为目前最准确、最高效和最全面的光学建模平台之一，还将在我们社区为开发创新的生物光子学技术、探索复杂的生物系统、促进可重复研究和在广泛的研究界之间建立高效合作建立新的标准。

 DESCRIPTION (provided by applicant): Novel biophotonics techniques continue to emerge at an unprecedented pace to address the rapidly expanding clinical needs for accurate, fast, non- or minimally-invasive quantification of physiology. A thorough understanding of the complex interaction between photons and biological tissues is at the very foundation of these techniques. Over the past 5 years, our group has been dedicated to the development of computationally efficient Monte Carlo (MC) methods for modeling light transport inside complex tissue structures. As a result of this research, two open-source simulation packages - Monte Carlo extreme (MCX) and Mesh-based Monte Carlo (MMC) - have been developed and disseminated. They are now driving research in many optics labs across the world as well as in small businesses, attested to by over 240 citations, more than 9,000 downloads and nearly 20,000 unique web visitors worldwide. In this proposal, we seek to further extend, solidify, and disseminate MCX and MMC, following the specific guidelines in NIH PA-14-156. Novel MC- based algorithms for modeling wide-field illumination and detection, rapid tomographic reconstructions and further speed acceleration will be developed and implemented to meet the escalating needs throughout the community towards developing the next-generation optical imaging techniques. As experienced open-source developers and maintainers, we embrace the pivotal role of engagement with our user community and plan to significantly enhance our software user experience, user support and systematic outreach and training. Towards significantly improved usability and scalability, we will develop web-based MCX/MMC to make our platform widely accessible, and a distributed computing cloud to enable fast processing of large, complex multi-modal datasets. We will also develop formal training courses and materials to better educate researchers, strengthen the support and feedback mechanisms, and work to create a standardized optical imaging data- exchange specification through our platform. Accomplishing these goals will not only make MCX/MMC one of the most accurate, efficient and comprehensive optical modeling platforms available, but also will set a new standard in our community for developing innovative biophotonics techniques, exploring complex biological systems, facilitating reproducible research and forging efficient collaboration among a broad research community.