Cloud MR: an Open-Source Software Framework to Democratize MRI Training and Research

Cloud MR：使 MRI 培训和研究大众化的开源软件框架

• 批准号: 10587391
• 负责人: Riccardo Lattanzi
• 金额: $ 62.57万
• 依托单位: NEW YORK UNIVERSITY SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-07-01 至 2026-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10587391
• 关键词: Algorithms; Anatomic Models; Asia; Biological; Brain imaging; Carbon; Clinical; Clinical Protocols; Cloud Computing; Complex; Computer software; Conceptions; Country; Data; Data Set; Democracy; Development; Documentation; Electromagnetic Fields; Engineering; Environmental Impact; Excision; Geometry; Goals; Image; Individual; Integral Equation; Internet; Intuition; Knee; Knowledge; Language; Magnetic Resonance; Magnetic Resonance Imaging; Methods; Modeling; Morphologic artifacts; Online Systems; Outcome; Patients; Performance; Physics; Physiologic pulse; Proliferating; Research; Research Personnel; Research Project Grants; Running; Sampling; Seminal; Shapes; Signal Transduction; Software Framework; Software Tools; Techniques; Technology; Testing; Time; Tissues; Training; Training and Education; Validation; computerized tools; contrast imaging; convolutional neural network; design; experimental study; flexibility; graphical user interface; image reconstruction; in vivo; innovation; magnetic field; models and simulation; neural network; new technology; novel; open data; open source; open source tool; prototype; radio frequency; radiologist; rational design; reconstruction; simulation; simulation environment; simulation software; skills; syntax; tool; transmission process; undergraduate student; virtual; virtual reality simulation; web-based tool

Project Summary/Abstract Cloud MR: an open-source software framework to democratize MRI training and research This project is a competing continuation of our project entitled Novel Software Tools for Rational Design and Assessment of MR Coils, which yielded seminal advances in understanding radiofrequency coil performance at high and ultra-high field. It also delivered novel computational tools for rapid coil simulation using Integral Equation techniques, and introduced the ultimate intrinsic transmit efficiency as an absolute metric for transmit coil performance. Our continuing project will integrate these advances into the development of Cloud MR, a comprehensive framework to simulate all aspects of the MRI experiment. By means of an intuitive web-based user interface, Cloud MR will allow the development of RF coils, pulse sequences and image reconstruction methods within an interconnected simulation environment that will enable users to optimize them jointly or individually. We will introduce the first web-based tool for modeling and simulation of flexible RF coils, as well as an innovative tool for pulse sequence development based on a Sequence Description Language. We will train a convolutional neural network for the removal of Gibbs artifacts using synthetic brain images generated with Cloud MR. The overall goal is to provide to anyone with an internet connection a powerful, innovative, comprehensive open-source tool for MRI research and training. By providing a virtual simulation environment to test new technology and optimize clinical protocols without operating an actual MR scanner, Cloud MR will reduce the carbon footprint of MRI. Cloud MR will also allow to generate realistic synthetic MR datasets to train neural networks, without the need to access actual patients’ data. We will distribute all software freely and fully documented, including tutorials and examples that could be used to demonstrate physics and engineering concepts in undergraduate and graduate courses.

项目总结/摘要 Cloud MR：一个使MRI培训和研究民主化的开源软件框架 这个项目是我们项目的一个竞争性的延续，该项目名为“用于Rational设计的新颖软件工具”， MR线圈的评估，在理解射频线圈性能方面取得了开创性进展， 高场和超高场。它还提供了新的计算工具，用于使用Integral进行快速线圈仿真 方程技术，并引入了最终的固有传输效率作为传输的绝对度量 线圈性能我们的持续项目将把这些进展整合到云MR的开发中， 全面的框架来模拟MRI实验的各个方面。通过直观的基于Web的 用户界面，云MR将允许开发RF线圈，脉冲序列和图像重建 互联仿真环境中的方法，使用户能够共同优化它们， 单独地我们将介绍第一个基于网络的工具，用于柔性RF线圈的建模和仿真，以及 一种基于序列描述语言的脉冲序列开发创新工具。我们将训练一个 卷积神经网络用于使用Cloud生成的合成大脑图像去除Gibbs伪影 先生总体目标是为任何有互联网连接的人提供一个强大的，创新的，全面的 MRI研究和培训的开源工具。通过提供虚拟仿真环境来测试新的 技术和优化临床协议，而无需操作实际的MR扫描仪，云MR将减少 核磁共振的碳足迹云MR还将允许生成逼真的合成MR数据集来训练神经网络。 网络，而无需访问实际患者的数据。我们将免费和完全地分发所有软件 文档，包括可用于演示物理和工程的教程和示例 本科和研究生课程中的概念。