Purpose: The aim of this work is to develop a high-performance, flexible and easy-to-use MRI reconstruction framework using the scientific programming language Julia. Methods: Julia is a modern, general purpose programming language with strong features in the area of signal / image processing and numerical computing. It has a high-level syntax but still generates efficient machine code that is usually as fast as comparable C/C++ applications. In addition to the language features itself, Julia has a sophisticated package management system that makes proper modularization of functionality across different packages feasible. Our developed MRI reconstruction framework MRIReco.jl can therefore reuse existing functionality from other Julia packages and concentrate on the MRI-related parts. This includes common imaging operators and support for MRI raw data formats. Results: MRIReco.jl is a simple to use framework with a high degree of accessibility. While providing a simple-to-use interface, many of its components can easily be extended and customized. The performance of MRIReco.jl is compared to the Berkeley Advanced Reconstruction Toolbox (BART) and we show that the Julia framework achieves comparable reconstruction speed as the popular C/C++ library. Conclusion: Modern programming languages can bridge the gap between high performance and accessible implementations. MRIReco.jl leverages this fact and contributes a promising environment for future algorithmic development in MRI reconstruction.
翻译:这项工作的目的是:利用科学编程语言Julia。方法:Julia是一种现代通用编程语言,在信号/图像处理和数字计算领域具有很强的特征。它具有高级语法,但仍能产生效率高的机器代码,通常与C/C+++/应用程序具有可比性。除了语言特点本身,Julia还拥有一个复杂的一揽子管理系统,使不同组合的功能能够适当模块化。因此,我们开发的MRI Reco.jl 能够重新利用其他Julia软件包的现有功能,并侧重于与MRI有关的部分。这包括通用成像操作员和支持MRI原始数据格式。结果:MRIReco.jl是一个简单易使用的框架,其使用速度通常与C/C+++应用程序一样快。除了语言特点之外,它的许多组成部分可以很容易扩展和定制。MRIReco.jl的绩效与Bergeester Reforst Reformation 工具箱(BARRT)相比,我们表明Julia框架在可访问性重建速度上与高C/C+Lismamainal Instrual developations 之间的差距,可以促进高C/Reval impal magistrucal ims mailmal mailmusmusmusmusmusmusal mailmals.