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dc.contributor.authorFedorov, Andriy
dc.contributor.authorLi, Xiaoxing
dc.contributor.authorPohl, Kilian M
dc.contributor.authorBouix, Sylvain
dc.contributor.authorStyner, Martin
dc.contributor.authorAddicott, Merideth
dc.contributor.authorWyatt, Chris
dc.contributor.authorDaunais, James B
dc.contributor.authorWells, William Mercer
dc.contributor.authorKikinis, Ron
dc.date.accessioned2012-08-08T14:55:46Z
dc.date.issued2011
dc.identifier.citationFedorov, Andriy, Xiaoxing Li, Kilian M Pohl, Sylvain Bouix, Martin Styner, Merideth Addicott, Chris Wyatt, James B Daunais, William M Wells, and Ron Kikinis. 2011. Atlas-guided segmentation of vervet monkey brain MRI. Open Neuroimaging Journal 5: 186-197.en_US
dc.identifier.issn1874-4400en_US
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:9369658
dc.description.abstractThe vervet monkey is an important nonhuman primate model that allows the study of isolated environmental factors in a controlled environment. Analysis of monkey MRI often suffers from lower quality images compared with human MRI because clinical equipment is typically used to image the smaller monkey brain and higher spatial resolution is required. This, together with the anatomical differences of the monkey brains, complicates the use of neuroimage analysis pipelines tuned for human MRI analysis. In this paper we developed an open source image analysis framework based on the tools available within the 3D Slicer software to support a biological study that investigates the effect of chronic ethanol exposure on brain morphometry in a longitudinally followed population of male vervets. We first developed a computerized atlas of vervet monkey brain MRI, which was used to encode the typical appearance of the individual brain structures in MRI and their spatial distribution. The atlas was then used as a spatial prior during automatic segmentation to process two longitudinal scans per subject. Our evaluation confirms the consistency and reliability of the automatic segmentation. The comparison of atlas construction strategies reveals that the use of a population-specific atlas leads to improved accuracy of the segmentation for subcortical brain structures. The contribution of this work is twofold. First, we describe an image processing workflow specifically tuned towards the analysis of vervet MRI that consists solely of the open source software tools. Second, we develop a digital atlas of vervet monkey brain MRIs to enable similar studies that rely on the vervet model.en_US
dc.language.isoen_USen_US
dc.publisherBentham Scienceen_US
dc.relation.isversionofdoi:10.2174/1874440001105010186en_US
dc.relation.hasversionhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC3256578/pdf/en_US
dash.licenseLAA
dc.titleAtlas-Guided Segmentation of Vervet Monkey Brain MRIen_US
dc.typeJournal Articleen_US
dc.description.versionVersion of Recorden_US
dc.relation.journalOpen Neuroimaging Journalen_US
dash.depositing.authorFedorov, Andriy
dc.date.available2012-08-08T14:55:46Z
dc.identifier.doi10.2174/1874440001105010186*
dash.contributor.affiliatedFedorov, Andriy
dash.contributor.affiliatedKikinis, Ron
dash.contributor.affiliatedWells, William
dash.contributor.affiliatedBouix, Sylvain


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