NIPreps: integrating neuroimaging preprocessing workflows across modalities, populations, and species

NIPreps：整合跨模式、人群和物种的神经影像预处理工作流程

• 批准号: 10513258
• 负责人: Russell A Poldrack
• 金额: $ 18.49万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-19 至 2024-07-18
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10513258
• 关键词: Address; Algorithms; Animal Model; Atlases; Automobile Driving; BRAIN initiative; Brain; Code; Collection; Communities; Computer Analysis; Computer software; Data; Data Aggregation; Data Analyses; Development; Devices; Diffusion; Diffusion Magnetic Resonance Imaging; Discipline; Documentation; Ecosystem; Educational Materials; Elderly; Ensure; Event; Experimental Designs; Foundations; Functional Magnetic Resonance Imaging; Generations; Human; Image; Investments; Libraries; Magnetic Resonance Imaging; Measurement; Measures; Mental disorders; Methodology; Methods; Modality; Monitor; Neurosciences; Pattern; Performance; Population; Positron-Emission Tomography; Process; Reporting; Reproducibility; Research; Research Personnel; Research Support; Scanning; Software Framework; Solid; Source; Specimen; Standardization; Statistical Data Interpretation; Statistical Models; Sum; System; Techniques; Translations; Visual; Visualization; Visualization software; arterial spin labeling; brain health; design; hackathon; heterogenous data; image reconstruction; imaging modality; imaging study; instrument; molecular imaging; morphometry; multimodality; neuroimaging; neuropsychiatric disorder; next generation; nonhuman primate; preclinical imaging; programs; sustainability framework; symposium; tool

We propose the NeuroImaging Preprocessing workflows ("NIPreps") framework, a workbench for the development of workflows and visualization tools for the preprocessing neuroimaging data. NiPreps expands our fMRIPrep software to operate on new imaging modalities and disciplines (e.g., preclinical imaging). Despite some remarkable analysis workflows that display end-to-end consolidation, integrations across applications (e.g., analyses of human and nonhuman data) remain exceptionally challenging. Next-generation neuroimaging workflows require harmonizing measures of wide-ranging phenomena (morphometry, functional activity, and connectivity) from multiple sources (e.g., scanning centers or modalities). Hence, we will evolve fMRIPrep into NiPreps, a software framework integrating BIDS and following the BIDS-Apps specifications. First, the project will consolidate the foundations of the NiPreps integration, with the generalization of fMRIPrep's driving principles and methods across modalities and domains of application. Second, we will expand the portfolio of end-user NiPreps with diffusion, arterial spin labeling (ASL), and molecular imaging "-Preps." Finally, we will address the consolidation of the NiPreps community to ensure the sustainability of the framework, converging the communities around fMRIPrep, dMRIPrep, ASLPrep, and PETPrep with hackathons and docusprints. In short, NIPreps will pave the way towards next-generation imaging, ultimately allowing neuroscientists to seek for a unified statistical framework that is capable of rigorously integrating cross-application and cross-species data analysis.

我们提出了神经成像预处理工作流程（“NIPreps”）框架，这是一个用于 开发用于预处理神经成像数据的工作流程和可视化工具。NiPreps扩展 我们的fMRIPrep软件可用于新的成像模式和学科（例如，临床前成像）。 尽管一些出色的分析工作流显示了端到端整合，但跨 应用程序（例如，人类和非人类数据的分析）仍然非常具有挑战性。下一代 神经成像工作流程需要协调各种现象的测量（形态测量， 功能活动和连接性）从多个源（例如，扫描中心或模态）。 因此，我们将把fMRIPrep演变成NiPreps，这是一个集成BIDS并遵循 BIDS-Apps规范。首先，该项目将巩固NiPreps整合的基础， fMRIPrep的驱动原理和方法的泛化跨模态和应用领域。 其次，我们将扩大最终用户NiPreps产品组合，包括扩散，动脉自旋标记（ASL）， 分子成像“-准备。“最后，我们将解决NiPreps社区的整合问题，以确保 框架的可持续性，围绕fMRIPrep，dMRIPrep，ASLPrep和 PETPrep有黑客马拉松和文档打印。简而言之，NIPreps将为下一代铺平道路 成像，最终使神经科学家能够寻求一个统一的统计框架， 严格整合跨应用程序和跨物种数据分析。