Magnetic Resonance Connectome Automated Pipeline: An Overview

Author

Gray, William R. ; Bogovic, John A. ; Vogelstein, Joshua T. ; Landman, Bennett A. ; Prince, Jerry L. ; Vogelstein, R. Jacob

Author_Institution

Appl. Phys. Lab., Johns Hopkins Univ., Laurel, MD, USA

Volume

3

Issue

2

fYear

2012

fDate

3/1/2012 12:00:00 AM

Firstpage

42

Lastpage

48

Abstract

This article presents a novel, tightly integrated pipeline for estimating a connectome. The pipeline utilizes magnetic resonance (MR) imaging (MRI) data to produce a high-level estimate of the structural connectivity in the human brain. The MR connectome automated pipeline (MRCAP) is efficient, and its modular construction allows researchers to modify algorithms to meet their specific requirements. The pipeline has been validated, and more than 200 connectomes have been processed and analyzed to date.

Keywords

biomedical MRI; brain; medical image processing; neurophysiology; pipeline processing; MR connectome automated pipeline; MRCAP; MRI data; connectome estimation; human brain structural connectivity; magnetic resonance connectome automated pipeline; magnetic resonance imaging; Brain models; Magnetic resonance imaging; Pipeline processing; Tensile stress; Algorithms; Brain; Databases, Factual; Diagnostic Techniques, Neurological; Humans; Magnetic Resonance Imaging; Nerve Net;

fLanguage

English

Journal_Title

Pulse, IEEE

Publisher

ieee

ISSN

2154-2287

Type

jour

DOI

10.1109/MPUL.2011.2181023

Filename

6173097