Research Topics
| D W ShattuckSummaryAffiliation: University of Southern California Country: USA Publications
| Collaborators
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Detail Information
Publications
Automated graph-based analysis and correction of cortical volume topologyD W Shattuck
Signal and Image Processing Institute, Department of Electrical Engineering Systems, University of Southern California, Los Angeles 90089 2564, USA
IEEE Trans Med Imaging 20:1167-77. 2001..A key benefit of the algorithm is that it localizes the change to a volume to the specific areas of its topological defects...
BrainSuite: an automated cortical surface identification toolDavid W Shattuck
Signal and Image Processing Institute, Department of Electrical Engineering Systems, University of Southern California, Los Angeles 90089 2564, USA
Med Image Anal 6:129-42. 2002..In this paper we describe the theory of each stage of the cortical surface identification process. We then present classification validation results using real and phantom data. We also present a study of interoperator variability...
Magnetic resonance image tissue classification using a partial volume modelD W Shattuck
Signal and Image Processing Institute, University of Southern California, Los Angeles, California 90089, USA
Neuroimage 13:856-76. 2001..Our method achieved average kappa indices kappa = 0.893 +/- 0.041 for GM and kappa = 0.928 +/- 0.039 for WM compared to the ground truth labeling on 12 volumes from the Montreal Neurological Institute's BrainWeb phantom...
Sulcal set optimization for cortical surface registrationAnand A Joshi
Signal and Image Processing Institute, University of Southern California, Los Angeles, CA 90089 2564, USA
Neuroimage 50:950-9. 2010..The optimal subsets of sulci are presented and the estimated and actual registration errors for these subsets are computed...
Internet2-based 3D PET image reconstruction using a PC clusterD W Shattuck
Signal and Image Processing Institute, University of Southern California, Los Angeles, CA 90089, USA
Phys Med Biol 47:2785-95. 2002..We report on the speed-up factors using the Beowulf approach and the impacts of communication latencies in the local cluster network and the network connection between the user's machine and our PC cluster...
A framework for registration, statistical characterization and classification of cortically constrained functional imaging dataAnand A Joshi
Signal and Image Processing Institute, University of Southern California, Los Angeles, CA 90089, USA
Inf Process Med Imaging 19:186-96. 2005....
Surface-constrained volumetric brain registration using harmonic mappingsAnand A Joshi
Image Processing Institute, University of Southern California, Los Angeles, CA 90089, USA
IEEE Trans Med Imaging 26:1657-69. 2007..We evaluate the performance of our proposed method relative to existing methods that use only intensity information; for this comparison we compute the intersubject alignment of expert-labeled subcortical structures after registration...
Comparison of landmark-based and automatic methods for cortical surface registrationDimitrios Pantazis
Signal and Image Processing Institute, University of Southern California, Los Angeles, CA 90089, USA
Neuroimage 49:2479-93. 2010..When automatic methods are used, the users should ensure that sulci in regions of interest in their studies are adequately aligned before proceeding with subsequent analysis...
Construction of a 3D probabilistic atlas of human cortical structuresDavid W Shattuck
Laboratory of Neuro Imaging, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, 635 Charles Young Drive South, NRB1, Suite 225, Los Angeles, CA 90095, USA
Neuroimage 39:1064-80. 2008....
Genetic algorithms for finite mixture model based voxel classification in neuroimagingJussi Tohka
Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, University of California, Los Angeles, CA 90095, USA
IEEE Trans Med Imaging 26:696-711. 2007..The tissue classification results by our method are shown to be consistently more reliable and accurate than with the competing parameter estimation methods...
Quantitative evaluation of automated skull-stripping methods applied to contemporary and legacy images: effects of diagnosis, bias correction, and slice locationChristine Fennema-Notestine
Laboratory of Cognitive Imaging, Department of Psychiatry, University of California, San Diego, and Veterans Affairs San Diego Healthcare System, San Diego, La Jolla, California 92093, USA
Hum Brain Mapp 27:99-113. 2006..The results of this study may direct users towards a method appropriate to their T1-weighted datasets and improve the efficiency of processing for large, multisite neuroimaging studies...
Cerebellar cortical atrophy in experimental autoimmune encephalomyelitisAllan MacKenzie-Graham
Laboratory of Neuro Imaging, Department of Neurology, University of California-Los Angeles, 635 Charles Young Drive South, Los Angeles, CA 90095-1769, USA
Neuroimage 32:1016-23. 2006..The model described herein can now be used to investigate neuropathologic mechanisms that lead to the development of gray matter atrophy in this setting...
Segmentation of skull and scalp in 3-D human MRI using mathematical morphologyBelma Dogdas
Signal and Image Processing Institute University of Southern California, Los Angeles, California 90089-2564, USA
Hum Brain Mapp 26:273-85. 2005....
A meta-algorithm for brain extraction in MRIDavid E Rex
Laboratory of Neuro Imaging, Department of Neurology, David Geffen School of Medicine at UCLA, 710 Westwood Plaza, Los Angeles, CA 90095-1769, USA
Neuroimage 23:625-37. 2004..BEMA outperformed the individual algorithms, as well as interrater results from a subset of the scans, when compared for the mean Dice coefficient, a rating of the similarity of output masks to the manually defined gold standards...
The informatics of a C57BL/6J mouse brain atlasAllan MacKenzie-Graham
Laboratory of Neuro Imaging, Department of Neurology, University of California, Los Angeles, CA, USA
Neuroinformatics 1:397-410. 2003..A comprehensive framework that encompasses many forms of information in the context of anatomic imaging holds tremendous promise for producing new insights. The atlas and associated tools can be found at http://www.loni.ucla.edu/MAP...
A multimodal, multidimensional atlas of the C57BL/6J mouse brainAllan MacKenzie-Graham
Laboratory of Neuro Imaging, Department of Neurology, University of California, Los Angeles, 710 Westwood Plaza, Room 4-238, Los Angeles, CA 90095-1769, USA
J Anat 204:93-102. 2004..Thus, the atlas becomes a framework for managing complex genetic and epigenetic information about the mouse brain. The atlas and associated tools may be accessed at http://www.loni.ucla.edu/MAP...
