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

基本信息

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
项目类别：
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

项目摘要

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.

项目概要/摘要 Cloud MR：一个开源软件框架，使 MRI 培训和研究民主化该项目是我们题为“用于理性设计和开发的新颖软件工具”的项目的竞争性延续。对 MR 线圈的评估，在了解射频线圈性能方面取得了开创性进展它还提供了使用 Integral 进行快速线圈仿真的新型计算工具。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我们的持续项目将把这些进步融入到 Cloud MR 的开发中。通过直观的基于网络的综合框架来模拟 MRI 实验的各个方面。 Cloud MR 用户界面将允许开发射频线圈、脉冲序列和图像重建互连仿真环境中的方法将使用户能够联合优化它们或我们将单独介绍第一个基于网络的工具，用于柔性射频线圈的建模和仿真。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。卷积神经网络使用云生成的合成大脑图像消除吉布斯伪影 MR. 的总体目标是为任何有互联网连接的人提供强大的、创新的、全面的服务。用于 MRI 研究和培训的开源工具，通过提供虚拟模拟环境来测试新功能。技术并优化临床方案而无需操作实际的 MR 扫描仪，Cloud MR 将减少 MRI 的碳足迹还可以生成真实的合成 MR 数据集来训练神经网络。网络，无需访问实际患者的数据，我们将免费且完整地分发所有软件。记录在案，包括可用于演示物理和工程的教程和示例本科生和研究生课程中的概念。