PhoenixMR: A GPU-based MRI simulation framework with runtime-dynamic code execution

IF 3.2 2区 医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Medical physics Pub Date : 2024-07-30 DOI:10.1002/mp.17273
Phillip Duncan-Gelder, Darin O'Keeffe, Phil Bones, Steven Marsh
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Abstract

Background

Simulations of physical processes and behavior can provide unique insights and understanding of real-world problems. Magnetic Resonance Imaging (MRI) is an imaging technique with several components of complexity. Several of these components have been characterized and simulated in the past. However, several computational challenges prevent simulations from being simultaneously fast, flexible, and accurate.

Purpose

The simulation of MRI experiments is underutilized by medical physicists and researchers using currently available simulators due to reasons including speed, accuracy, and extensibility constraints. This paper introduces an innovative MRI simulation engine and framework that aims to overcome these issues making available realistic and fast MRI simulation.

Methods

Using the CUDA C/C++ programing language, an MRI simulation engine (PhoenixMR), incorporating a Turing-complete virtual machine (VM) to simulate abstract spatiotemporal complexities, was developed. This engine solves a set of time-discrete Bloch equations using the symmetric operator splitting technique. An extensible front-end framework package (written in Python) aids the use of PhoenixMR to simplify simulation development.

Results

The PhoenixMR library and front-end codes have been developed and tested. A set of example simulations were performed to demonstrate the ease of use and flexibility of simulation components such as geometrical setup, pulse sequence design, phantom design, and so forth. Initial validation of PhoenixMR is performed by comparing its accuracy and performance against a widely used MRI simulator using identical simulation parameters. Validation results show PhoenixMR simulations are three orders of magnitude faster. There is also strong agreement between models.

Conclusions

A novel MRI simulation platform called PhoenixMR has been introduced. This research tool is designed to be usable by physicists and engineers interested in performing MRI simulations. Examples are shown demonstrating the accuracy, flexibility, and usability of PhoenixMR in several key areas of MRI simulation.

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PhoenixMR:基于 GPU 的磁共振成像仿真框架,具有运行时动态代码执行功能。
背景:对物理过程和行为的模拟可以提供独特的洞察力和对现实世界问题的理解。磁共振成像(MRI)是一种成像技术,具有多个复杂的组成部分。过去曾对其中几个组件进行过表征和模拟。目的:由于速度、准确性和可扩展性限制等原因,医学物理学家和研究人员使用现有模拟器对核磁共振成像实验的模拟利用不足。本文介绍了一种创新的核磁共振成像仿真引擎和框架,旨在克服这些问题,提供逼真、快速的核磁共振成像仿真:方法:使用 CUDA C/C++ 编程语言,开发了一个磁共振成像仿真引擎(PhoenixMR),其中包含一个图灵完备的虚拟机(VM),用于仿真抽象的时空复杂性。该引擎利用对称算子分裂技术求解一组时间离散布洛赫方程。一个可扩展的前端框架包(用 Python 编写)可帮助使用 PhoenixMR,简化仿真开发:PhoenixMR 库和前端代码已经开发完成并经过测试。结果:PhoenixMR 库和前端代码已经开发完成并经过测试,还进行了一系列示例仿真,以展示仿真组件的易用性和灵活性,如几何设置、脉冲序列设计、假体设计等。通过使用相同的模拟参数将 PhoenixMR 的准确性和性能与广泛使用的磁共振成像模拟器进行比较,对 PhoenixMR 进行了初步验证。验证结果表明,PhoenixMR 的模拟速度快了三个数量级。各模型之间也有很强的一致性:本文介绍了一种名为 PhoenixMR 的新型磁共振成像模拟平台。该研究工具旨在供对磁共振成像仿真感兴趣的物理学家和工程师使用。示例展示了 PhoenixMR 在核磁共振成像仿真的几个关键领域中的准确性、灵活性和可用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Medical physics
Medical physics 医学-核医学
CiteScore
6.80
自引率
15.80%
发文量
660
审稿时长
1.7 months
期刊介绍: Medical Physics publishes original, high impact physics, imaging science, and engineering research that advances patient diagnosis and therapy through contributions in 1) Basic science developments with high potential for clinical translation 2) Clinical applications of cutting edge engineering and physics innovations 3) Broadly applicable and innovative clinical physics developments Medical Physics is a journal of global scope and reach. By publishing in Medical Physics your research will reach an international, multidisciplinary audience including practicing medical physicists as well as physics- and engineering based translational scientists. We work closely with authors of promising articles to improve their quality.
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