2012
DOI: 10.1016/j.neuroimage.2012.07.021
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Quantitative mouse brain phenotyping based on single and multispectral MR protocols

Abstract: Sophisticated image analysis methods have been developed for the human brain, but such tools still need to be adapted and optimized for quantitative small animal imaging. We propose a framework for quantitative anatomical phenotyping in mouse models of neurological and psychiatric conditions. The framework encompasses an atlas space, image acquisition protocols, and software tools to register images into this space. We show that a suite of segmentation tools (Avants, Epstein et al., 2008) designed for human ne… Show more

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Cited by 32 publications
(32 citation statements)
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“…One caveat that must be appreciated is that analyses of volume and intensity changes are only as accurate as the registration method employed. Registration accuracy of these algorithms has been previously assessed (Badea et al, 2012; Klein et al, 2009; Spring et al, 2007; van Eede et al, 2013) and shown to be able to detect subtle alterations (5% or less) in anatomy between mice as well as accurately segmenting anatomical brain regions (Chakravarty et al, 2013). Structure-wise analyses of brain regions, after automated segmentation, should be less sensitive to errors than voxel-wise analyses, with both methods showing promise for detecting and analyzing mutant phenotypes in the developing mouse brain (Szulc et al, 2013).…”
Section: Discussionmentioning
confidence: 99%
“…One caveat that must be appreciated is that analyses of volume and intensity changes are only as accurate as the registration method employed. Registration accuracy of these algorithms has been previously assessed (Badea et al, 2012; Klein et al, 2009; Spring et al, 2007; van Eede et al, 2013) and shown to be able to detect subtle alterations (5% or less) in anatomy between mice as well as accurately segmenting anatomical brain regions (Chakravarty et al, 2013). Structure-wise analyses of brain regions, after automated segmentation, should be less sensitive to errors than voxel-wise analyses, with both methods showing promise for detecting and analyzing mutant phenotypes in the developing mouse brain (Szulc et al, 2013).…”
Section: Discussionmentioning
confidence: 99%
“…Despite this necessary design limitation, the consistency in our findings across imaging modalities would suggest that volumetric differences either do not exist or that their detection requires much higher resolution than was used by our studies. Others have reported on the comparability of various imaging methods, and found relatively high correspondence of results (Bedea et at., 2012)…”
Section: Discussionmentioning
confidence: 87%
“…To evaluate regional differences in the neuroanatomy and DTI parameters between CVN-AD mice and controls, we used a segmentation pipeline (Badea et al, 2012) translated into a high-performance computing environment. We wrote Perl modules to parallelize pairwise registrations and perform voxel-based analysis on a 7-node cluster, managing SLURM jobs using Bright Cluster Manager.…”
Section: Methodsmentioning
confidence: 99%