Literature DB >> 21278014

Diffeomorphic brain registration under exhaustive sulcal constraints.

Guillaume Auzias1, Olivier Colliot, Joan Alexis Glaunès, Matthieu Perrot, Jean-François Mangin, Alain Trouvé, Sylvain Baillet.   

Abstract

The alignment and normalization of individual brain structures is a prerequisite for group-level analyses of structural and functional neuroimaging data. The techniques currently available are either based on volume and/or surface attributes, with limited insight regarding the consistent alignment of anatomical landmarks across individuals. This article details a global, geometric approach that performs the alignment of the exhaustive sulcal imprints (cortical folding patterns) across individuals. This DIffeomorphic Sulcal-based COrtical (DISCO) technique proceeds to the automatic extraction, identification and simplification of sulcal features from T1-weighted Magnetic Resonance Image (MRI) series. These features are then used as control measures for fully-3-D diffeomorphic deformations. Quantitative and qualitative evaluations show that DISCO correctly aligns the sulcal folds and gray and white matter volumes across individuals. The comparison with a recent, iconic diffeomorphic approach (DARTEL) highlights how the absence of explicit cortical landmarks may lead to the misalignment of cortical sulci. We also feature DISCO in the automatic design of an empirical sulcal template from group data. We also demonstrate how DISCO can efficiently be combined with an image-based deformation (DARTEL) to further improve the consistency and accuracy of alignment performances. Finally, we illustrate how the optimized alignment of cortical folds across subjects improves sensitivity in the detection of functional activations in a group-level analysis of neuroimaging data.

Mesh:

Year:  2011        PMID: 21278014     DOI: 10.1109/TMI.2011.2108665

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  16 in total

1.  BIRNet: Brain image registration using dual-supervised fully convolutional networks.

Authors:  Jingfan Fan; Xiaohuan Cao; Pew-Thian Yap; Dinggang Shen
Journal:  Med Image Anal       Date:  2019-03-22       Impact factor: 8.545

Review 2.  Deformable medical image registration: a survey.

Authors:  Aristeidis Sotiras; Christos Davatzikos; Nikos Paragios
Journal:  IEEE Trans Med Imaging       Date:  2013-05-31       Impact factor: 10.048

3.  Hierarchical unbiased graph shrinkage (HUGS): a novel groupwise registration for large data set.

Authors:  Shihui Ying; Guorong Wu; Qian Wang; Dinggang Shen
Journal:  Neuroimage       Date:  2013-09-19       Impact factor: 6.556

4.  Diffeomorphic sulcal shape analysis on the cortex.

Authors:  Shantanu H Joshi; Ryan P Cabeen; Anand A Joshi; Bo Sun; Ivo Dinov; Katherine L Narr; Arthur W Toga; Roger P Woods
Journal:  IEEE Trans Med Imaging       Date:  2012-02-06       Impact factor: 10.048

5.  Validation of a nonrigid registration error detection algorithm using clinical MRI brain data.

Authors:  Ryan D Datteri; Yuan Liu; Pierre-Francois D'Haese; Benoit M Dawant
Journal:  IEEE Trans Med Imaging       Date:  2014-07-30       Impact factor: 10.048

6.  Surface fluid registration of conformal representation: application to detect disease burden and genetic influence on hippocampus.

Authors:  Jie Shi; Paul M Thompson; Boris Gutman; Yalin Wang
Journal:  Neuroimage       Date:  2013-04-13       Impact factor: 6.556

7.  Landmark-guided region-based spatial normalization for functional magnetic resonance imaging.

Authors:  Hengda He; Qolamreza R Razlighi
Journal:  Hum Brain Mapp       Date:  2022-04-12       Impact factor: 5.399

8.  Automated parcellation of the brain surface generated from magnetic resonance images.

Authors:  Wen Li; Nancy C Andreasen; Peg Nopoulos; Vincent A Magnotta
Journal:  Front Neuroinform       Date:  2013-10-22       Impact factor: 4.081

9.  Computational analysis of LDDMM for brain mapping.

Authors:  Can Ceritoglu; Xiaoying Tang; Margaret Chow; Darian Hadjiabadi; Damish Shah; Timothy Brown; Muhammad H Burhanullah; Huong Trinh; John T Hsu; Katarina A Ament; Deana Crocetti; Susumu Mori; Stewart H Mostofsky; Steven Yantis; Michael I Miller; J Tilak Ratnanather
Journal:  Front Neurosci       Date:  2013-08-27       Impact factor: 4.677

10.  eHUGS: Enhanced Hierarchical Unbiased Graph Shrinkage for Efficient Groupwise Registration.

Authors:  Guorong Wu; Xuewei Peng; Shihui Ying; Qian Wang; Pew-Thian Yap; Dan Shen; Dinggang Shen
Journal:  PLoS One       Date:  2016-01-22       Impact factor: 3.240

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