Continued Development and Maintenance of MriStudio

MriStudio的持续开发和维护

• 批准号: 9118340
• 负责人: MICHAEL I MILLER
• 金额: $ 35.44万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2018-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9118340
• 关键词: Adopted; Algorithms; Anatomy; Architecture; Archives; Atlases; Base of the Brain; Brain Mapping; Collaborations; Communities; Computer Analysis; Computer software; Data; Databases; Dependence; Development; Diffusion Magnetic Resonance Imaging; Environment; Grant; Hand; Health; Image; Image Analysis; Link; Magnetic Resonance Imaging; Maintenance; Manuals; Memory; Methods; Multicenter Studies; Online Systems; Process; Quality Control; Reporting; Research; Resolution; Resources; Services; Supercomputing; System; Technology; Testing; Training; Universities; Update; Visit; base; image processing; imaging Segmentation; improved; neuroimaging; platform-independent; programs; research study; software development; symposium; technology diffusion; tool; web based interface; web interface; white matter

DESCRIPTION (provided by applicant): The purpose of this grant is to support continued development and maintenance of MriStudio software developed in Johns Hopkins University. MriStudio is comprehensive software for MR image processing and analysis with emphasis on white matter anatomy. MriStudio consists of three modules, DtiStudio, DiffeoMap, and RoiEditor. DtiStudio was introduced in 2001 and remains one of the most widely used programs to process diffusion tensor imaging (DTI) data. DiffeoMap and RoiEditor were introduced in 2007, which provides a very unique environment to perform a cutting-edge image transformation and atlas-based automated image segmentation. What is especially unique about DiffeoMap is, because our advanced brain mapping algorithms are highly CPU and memory intensive, it adopts Cloud-type architecture, through which users can have access to our supercomputation resource. Currently, there are more than 6,500 registered uses. In this application, we propose to extend this service to the community through the following aims; Aim 1: Continued user support through training and dissemination Currently, two major channels of training and dissemination are through web-based resources (manuals and videos) and hand-on monthly 2-day tutorials. As the functionalities of MriStudio expand, we will continuously update the online materials and tutorials. Aim 2: Extension of the functionality Aim 2-1: Advanced diffusion MRI analysis package: Through the collaboration with Dr. Tournier, spherical harmonic decomvolution algorithm will be implemented. Aim 2-2: Automated and probabilistic tractography: We will incorporate a probabilistic tractography method based on dynamic programing and automate the ROI definition process. Aim 2-3: Quality control reporting: We will deploy a comprehensive and quantitative quality control reporting system, which is extremely important for automated analysis of large-scale studies. Aim 3: Cross-platform extension by adopting web-based interface. We will develop web-based Cloud computation service, which will eliminate the platform-dependence. Aim 4: Completion of XNAT-based solution, we will develop a server-based automated analysis pipeline that is linked to a research image database system, called XNAT. Aim 5: Deployment of multi-atlas-based brain segmentation algorithm, we will deploy our multi-atlas technology in our server and make them available for testing to users through the Cloud computation system.

描述（由申请人提供）：这笔赠款的目的是支持约翰·霍普金斯大学开发的MRISTUDIO软件的持续开发和维护。 Mristudio是用于MR图像处理和分析的综合软件，重点是白质解剖结构。 Mristudio由三个模块，Dtistudio，DiffeoMap和Roieditor组成。 Dtistudio于2001年推出，仍然是处理扩散张量成像（DTI）数据的最广泛使用的程序之一。 DiffeoMap和Roieditor于2007年引入，该环境提供了一个非常独特的环境，可以执行最先进的图像转换和基于ATLAS的自动图像分割。 DIFFEOMAP特别独特的是，因为我们先进的大脑映射算法是高度CPU和内存密集型的，因此它采用了云型体系结构，用户可以通过该体系结构访问我们的超级计算资源。当前，有6,500多种注册用途。在此应用程序中，我们建议通过以下目标将此服务扩展到社区； AIM 1：通过培训和传播目前的持续用户支持，两个主要的培训和传播渠道是通过基于Web的资源（手册和视频）和每月2天的手工完成的。随着MRISTUDIO的功能扩大，我们将不断更新在线材料和教程。 AIM 2：功能的扩展目标目标2-1：高级扩散MRI分析套件：通过与Tournier博士的合作，将实施球形谐波分流算法。 AIM 2-2：自动化和概率的拖拉术：我们将基于动态编程的概率拖拉方法合并，并自动化ROI定义过程。 AIM 2-3：质量控制报告：我们将部署全面和定量的质量控制报告系统，这对于大规模研究的自动分析非常重要。 AIM 3：通过采用基于Web的接口，跨平台扩展。 我们将开发基于Web的云计算服务，这将消除平台依赖性。 AIM 4：基于XNAT的解决方案的完成，我们将开发基于服务器的自动分析管道，该管道链接到一个名为XNAT的研究图像数据库系统。 AIM 5：部署基于多ATLA的大脑细分算法，我们将在服务器中部署多ATLAS技术，并通过云计算系统向用户进行测试。