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

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

Comput Biol Med. 2010 Mar;40(3):279-87. doi: 10.1016/j.compbiomed.2009.12.003. Epub 2010 Jan 13.

Authors

Christof Karmonik¹, Michele York, Robert Grossman, Ekta Kakkar, Krutina Patel, Hani Haykal, David King

Affiliation

¹ Department of Neurosurgery, The Methodist Hospital, Houston, TX, USA. ckarmonik@tmhs.org

PMID: 20074720
DOI: 10.1016/j.compbiomed.2009.12.003

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.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Automation*
Image Processing, Computer-Assisted*
Magnetic Resonance Imaging / methods*
National Institutes of Health (U.S.)
Software*
United States