DOI: 10.1007/978-3-540-69497-7_46
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IRMA: An Image Registration Meta-algorithm

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Cited by 7 publications
(4 citation statements)
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“…Figure 1 shows the pipeline workflow implementing the volumetric data analysis. The volumetric workflow pipeline consists of 4 main components– data preprocessing (intensity inhomogeneity correction [118] and skull-stripping [83; 84], cortical surface modeling [48], and tissue classification [134; 135]. The complete pipeline workflows are available as XML objects which can be downloaded, viewed and tested via the Pipeline environment (pipeline.loni.ucla.edu), see supplementary Files 1 and 2.…”
Section: 10 Methodsmentioning
confidence: 99%
“…Figure 1 shows the pipeline workflow implementing the volumetric data analysis. The volumetric workflow pipeline consists of 4 main components– data preprocessing (intensity inhomogeneity correction [118] and skull-stripping [83; 84], cortical surface modeling [48], and tissue classification [134; 135]. The complete pipeline workflows are available as XML objects which can be downloaded, viewed and tested via the Pipeline environment (pipeline.loni.ucla.edu), see supplementary Files 1 and 2.…”
Section: 10 Methodsmentioning
confidence: 99%
“…The University of Southern California Laboratory of Neuroimaging pipeline ( http://pipeline.loni.usc.edu/ ), a graphical workflow environment was utilized for image preprocessing and CT and GMV analyses. All structural scans were first converted from DICOM to NIFTI, a format that could be analyzed, including intensity inhomogeneity correction,[ 35 ] skull-stripping,[ 36 , 37 ] and cortical surface modeling. [ 38 ] Gray matter thickness and volume were estimated using a well-validated method[ 39 ] implemented in FreeSurfer 4.0[ 38 ] (available free to the public, http://surfer.nmr.mgh.harvard.edu/fswiki and http://ucla.in/xSQPqT ).…”
Section: Methodsmentioning
confidence: 99%
“…A whole-brain binary mask and brain tissue type classification (GM, WM, and cerebrospinal fluid) were generated for each participant's raw baseline scan using a skull-stripping meta-algorithm. 31,32 This algorithm uses a skull-stripped reference image and identifies a consensus-based brain mask based on the results of several independent skull-stripping algorithms. The skull-stripped brain image data were then converted to binary masks and manually edited to eliminate any segmentation errors.…”
Section: Methodsmentioning
confidence: 99%