Ten years of k-Wave: a review of the past and a roadmap for the future (Conference Presentation)

B. Treeby, J. Jaros, Filip Vaverka, J. Budisky, Marta Cudova, Kristian Kadlubiak, Petr Kleparnik, Filip Kuklis, Elliott S. Wise, P. Georgiou, E. Martin, James Robertson, F. Lucka, B. Cox
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Abstract

k-Wave is an open-source MATLAB toolbox designed for the time-domain simulation of propagating acoustic waves in 1D, 2D, or 3D. The first release was in 2009, and focused on the simulation of photoacoustic initial value problems and the reconstruction of photoacoustic images from simulated or experimental data. In the ten years since, there have been eight major releases, extending both the functionality and the computational performance of the toolbox. There are now more than 10,000 registered users worldwide, and the toolbox has become the defacto standard for simulation studies in photoacoustic imaging. The development team responsible for k-Wave has also grown, with expertise now spanning physics, mathematics, inverse problems, numerical methods, software engineering, and high-performance computing. In this presentation, the major theoretical, algorithmic, and computational developments of k-Wave will be described, along with the underlying design inputs and decisions that led to these developments. A roadmap for the future development of k-Wave will also be presented. This includes new transducer classes, stair-case free sources, native support for multiple GPUs, adaptive grid refinement using moving mesh methods, gradient-based iterative photoacoustic image reconstruction, performance and accuracy improvements for the elastic wave models, and automatic job-submission to run k-Wave simulations remotely using HPC-as-a-service.
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k-Wave的十年:过去的回顾和未来的路线图(会议报告)
k-Wave是一个开源的MATLAB工具箱,专为一维、二维或三维声波传播的时域模拟而设计。第一次发布是在2009年,重点是光声初值问题的模拟以及从模拟或实验数据中重建光声图像。从那以后的十年里,已经有八个主要版本,扩展了工具箱的功能和计算性能。目前全球已有超过10,000名注册用户,该工具箱已成为光声成像模拟研究的事实上的标准。负责k-Wave的开发团队也在不断壮大,其专业知识现已跨越物理、数学、反问题、数值方法、软件工程和高性能计算。在本演讲中,将描述k-Wave的主要理论、算法和计算发展,以及导致这些发展的底层设计输入和决策。此外,还将发表k-Wave的未来发展蓝图。这包括新的换能器类、无阶梯源、对多个gpu的本地支持、使用移动网格方法的自适应网格细化、基于梯度的迭代光声图像重建、弹性波模型的性能和精度改进,以及使用hpc即服务远程运行k-Wave模拟的自动作业提交。
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