An image analysis pipeline for the semi-automated analysis of clinical fMRI images based on freely available software

Christof Karmonik; Michele York; Robert G. Grossman; Ekta Kakkar; Krutina Patel; Hani Haykal; David E. King

doi:10.1016/j.compbiomed.2009.12.003

An image analysis pipeline for the semi-automated analysis of clinical fMRI images based on freely available software

Christof Karmonik, Michele York, Robert G. Grossman, Ekta Kakkar, Krutina Patel, Hani Haykal, David E. King

Research output: Contribution to journal › Article › peer-review

7 Scopus citations

Abstract

The technique of functional Magnetic Resonance Imaging (fMRI) has evolved in the last 15 years from a research concept into a clinically relevant medical procedure. In this study, an efficient, semi-automated and cost-effective solution for the analysis of fMRI images acquired in a clinical setting is presented relying heavily on open source software. The core of the pipeline is the software Analysis of Functional NeuroImages (AFNI, National Institute of Mental Health (NIMH)) combined with K-PACS and ImageJ. Its application is illustrated with clinical fMRI exams and with a research study involving comparing subjects diagnosed with Parkinson's disease and age-matched controls.

Original language	English (US)
Pages (from-to)	279-287
Number of pages	9
Journal	Computers in Biology and Medicine
Volume	40
Issue number	3
DOIs	https://doi.org/10.1016/j.compbiomed.2009.12.003
State	Published - Mar 2010

Keywords

Automated image analysis
Brain activation
Clinical fMRI
Functional magnetic resonance imaging
Image analysis pipeline

ASJC Scopus subject areas

Computer Science Applications
Health Informatics

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10.1016/j.compbiomed.2009.12.003

Cite this

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abstract = "The technique of functional Magnetic Resonance Imaging (fMRI) has evolved in the last 15 years from a research concept into a clinically relevant medical procedure. In this study, an efficient, semi-automated and cost-effective solution for the analysis of fMRI images acquired in a clinical setting is presented relying heavily on open source software. The core of the pipeline is the software Analysis of Functional NeuroImages (AFNI, National Institute of Mental Health (NIMH)) combined with K-PACS and ImageJ. Its application is illustrated with clinical fMRI exams and with a research study involving comparing subjects diagnosed with Parkinson's disease and age-matched controls.",

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note = "Funding Information: Funding support from the Methodist Hospital Research Institute in form of a Scholarship grant for the Neuroimaging research study is gratefully acknowledged. Copyright: Copyright 2010 Elsevier B.V., All rights reserved.",

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AU - Patel, Krutina

AU - Haykal, Hani

AU - King, David E.

N1 - Funding Information: Funding support from the Methodist Hospital Research Institute in form of a Scholarship grant for the Neuroimaging research study is gratefully acknowledged. Copyright: Copyright 2010 Elsevier B.V., All rights reserved.

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An image analysis pipeline for the semi-automated analysis of clinical fMRI images based on freely available software

Abstract

Keywords

ASJC Scopus subject areas

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