MRIO: the Magnetic Resonance Imaging Acquisition and Analysis Ontology.

IF 2.7 4区 医学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Neuroinformatics Pub Date : 2024-07-01 Epub Date: 2024-05-20 DOI:10.1007/s12021-024-09664-8
Alexander Bartnik, Lucas M Serra, Mackenzie Smith, William D Duncan, Lauren Wishnie, Alan Ruttenberg, Michael G Dwyer, Alexander D Diehl
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Abstract

Magnetic resonance imaging of the brain is a useful tool in both the clinic and research settings, aiding in the diagnosis and treatments of neurological disease and expanding our knowledge of the brain. However, there are many challenges inherent in managing and analyzing MRI data, due in large part to the heterogeneity of data acquisition. To address this, we have developed MRIO, the Magnetic Resonance Imaging Acquisition and Analysis Ontology. MRIO provides well-reasoned classes and logical axioms for the acquisition of several MRI acquisition types and well-known, peer-reviewed analysis software, facilitating the use of MRI data. These classes provide a common language for the neuroimaging research process and help standardize the organization and analysis of MRI data for reproducible datasets. We also provide queries for automated assignment of analyses for given MRI types. MRIO aids researchers in managing neuroimaging studies by helping organize and annotate MRI data and integrating with existing standards such as Digital Imaging and Communications in Medicine and the Brain Imaging Data Structure, enhancing reproducibility and interoperability. MRIO was constructed according to Open Biomedical Ontologies Foundry principles and has contributed several classes to the Ontology for Biomedical Investigations to help bridge neuroimaging data to other domains. MRIO addresses the need for a "common language" for MRI that can help manage the neuroimaging research, by enabling researchers to identify appropriate analyses for sets of scans and facilitating data organization and reporting.

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MRIO:磁共振成像获取与分析本体论。
脑部磁共振成像是临床和研究领域的有用工具,有助于诊断和治疗神经系统疾病,并扩展我们对大脑的认识。然而,在管理和分析核磁共振成像数据方面存在许多固有的挑战,这在很大程度上是由于数据采集的异质性造成的。为了解决这个问题,我们开发了 MRIO(磁共振成像获取与分析本体)。MRIO 为几种磁共振成像采集类型的采集和著名的同行评议分析软件提供了合理的类和逻辑公理,从而促进了磁共振成像数据的使用。这些类为神经成像研究过程提供了一种通用语言,并有助于将核磁共振成像数据的组织和分析标准化,从而获得可重复的数据集。我们还提供查询功能,用于自动分配给定磁共振成像类型的分析。MRIO 帮助研究人员组织和注释核磁共振成像数据,并与现有标准(如医学数字成像与通信标准和脑成像数据结构标准)集成,从而提高可重复性和互操作性,从而帮助研究人员管理神经成像研究。MRIO 是根据开放生物医学本体论基金会的原则构建的,并为生物医学调查本体论贡献了几个类,以帮助将神经成像数据与其他领域连接起来。MRIO 满足了对 MRI "通用语言 "的需求,可帮助管理神经成像研究,使研究人员能够为扫描集确定适当的分析,并促进数据组织和报告。
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来源期刊
Neuroinformatics
Neuroinformatics 医学-计算机:跨学科应用
CiteScore
6.00
自引率
6.70%
发文量
54
审稿时长
3 months
期刊介绍: Neuroinformatics publishes original articles and reviews with an emphasis on data structure and software tools related to analysis, modeling, integration, and sharing in all areas of neuroscience research. The editors particularly invite contributions on: (1) Theory and methodology, including discussions on ontologies, modeling approaches, database design, and meta-analyses; (2) Descriptions of developed databases and software tools, and of the methods for their distribution; (3) Relevant experimental results, such as reports accompanie by the release of massive data sets; (4) Computational simulations of models integrating and organizing complex data; and (5) Neuroengineering approaches, including hardware, robotics, and information theory studies.
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