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

  • Authors:

  • Christof Karmonik;Michele York;Robert Grossman;Ekta Kakkar;Krutina Patel;Hani Haykal;David King

  • Affiliations:

  • Department of Neurosurgery, The Methodist Hospital, Houston, TX, USA;Michele York, Department of Neurology, Baylor College of Medicine, Houston, TX, USA;Department of Neurosurgery, The Methodist Hospital, Houston, TX, USA;Department of Neurosurgery, The Methodist Hospital, Houston, TX, USA;Department of Neurosurgery, The Methodist Hospital, Houston, TX, USA;Department of Radiology, The Methodist Hospital, Houston, TX, USA;Department of Radiology, The Methodist Hospital, Houston, TX, USA

  • Venue:
  • Computers in Biology and Medicine
  • Year:
  • 2010

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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.