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Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...
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Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
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Published on: July 1, 2014

Ontology for FMRI as a biomedical informatics method.

Toshiharu Nakai1, Epifanio Bagarinao, Yoshio Tanaka

  • 1Functional Brain Imaging Lab, Department of Gerontechnology, National Center for Geriatrics and Gerontology, Aichi, Japan. toshi@nils.go.jp

Magnetic Resonance in Medical Sciences : MRMS : an Official Journal of Japan Society of Magnetic Resonance in Medicine
|October 2, 2008
PubMed
Summary

Ontological engineering is crucial for integrating biomedical data. Developing neuroimaging ontologies, like the fMRI ontology in BAXGRID, bridges semantic gaps between modalities for better information retrieval.

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Area of Science:

  • Biomedical Informatics
  • Neuroimaging
  • Ontological Engineering

Background:

  • Ontological engineering is vital for integrating heterogeneous biomedical databases.
  • Ontologies provide a framework for computer processing of complex biological information.
  • Clinical functional neuroimaging requires integrating multimodal brain data.

Purpose of the Study:

  • To develop an ontology for clinical functional neuroimaging.
  • To address the challenge of integrating heterogeneous neuroimaging data.
  • To bridge semantic gaps among neuroimaging modalities.

Main Methods:

  • Developing a neuroimaging ontology detailing hypotheses, paradigms, and data generation.
  • Utilizing High-performance, Global Resource Information Database (GRID) computing and Service-Oriented Computing (SOC).
  • Creating a distributed intelligent neuroimaging system (BAXGRID) for real-time fMRI analysis.

Main Results:

  • Established a neuroimaging ontology framework.
  • Developed the BAXGRID system for real-time fMRI analysis.
  • Planned integration of the fMRI ontology with existing medical ontologies like UMLS.

Conclusions:

  • Neuroimaging ontologies are indispensable for integrating multimodal brain imaging data.
  • Ontology development facilitates semantic interoperability among neuroimaging modalities.
  • Distributed computing and service-oriented architectures support complex neuroimaging data integration.