Literature DB >> 27169137

Topography-Based Registration of Developing Cortical Surfaces in Infants Using Multidirectional Varifold Representation.

Islem Rekik1, Gang Li1, Weili Lin1, Dinggang Shen1.   

Abstract

Cortical surface registration or matching facilitates atlasing, cortical morphology-function comparison and statistical analysis. Methods that geodesically shoot surfaces into one another, as currents or varifolds, provide an elegant mathematical framework for generic surface matching and dynamic local features estimation, such as deformation momenta. However, conventional current and varifold matching methods only use the normals of the surface to measure its geometry and guide the warping process, which overlooks the importance of the direction in the convoluted cortical sulcal and gyral folds. To cope with the stated limitation, we decompose each cortical surface into its normal and tangent varifold representations, by integrating principal curvature direction field into the varifold matching framework, thus providing rich information for the direction of cortical folding and better characterization of the cortical geometry. To include more informative cortical geometric features in the matching process, we adaptively place control points based on the surface topography, hence the deformation is controlled by points lying on gyral crests (or "hills") and sulcal fundi (or "valleys") of the cortical surface, which are the most reliable and important topographic and anatomical landmarks on the cortex. We applied our method for registering the developing cortical surfaces in 12 infants from 0 to 6 months of age. Both of these variants significantly improved the matching accuracy in terms of closeness to the target surface and the precision of alignment with regional anatomical boundaries, when compared with several state-of-the-art methods: (1) diffeomorphic spectral matching, (2) current-based surface matching and (3) original varifold-based surface matching.

Entities:  

Year:  2015        PMID: 27169137      PMCID: PMC4860272          DOI: 10.1007/978-3-319-24571-3_28

Source DB:  PubMed          Journal:  Med Image Comput Comput Assist Interv


  8 in total

1.  High-resolution intersubject averaging and a coordinate system for the cortical surface.

Authors:  B Fischl; M I Sereno; R B Tootell; A M Dale
Journal:  Hum Brain Mapp       Date:  1999       Impact factor: 5.038

2.  Oriented morphometry of folds on surfaces.

Authors:  Maxime Boucher; Alan Evans; Kaleem Siddiqi
Journal:  Inf Process Med Imaging       Date:  2009

3.  Statistical models of sets of curves and surfaces based on currents.

Authors:  Stanley Durrleman; Xavier Pennec; Alain Trouvé; Nicholas Ayache
Journal:  Med Image Anal       Date:  2009-07-17       Impact factor: 8.545

4.  Diffeomorphic spectral matching of cortical surfaces.

Authors:  Herve Lombaert; Jon Sporring; Kaleem Siddiqi
Journal:  Inf Process Med Imaging       Date:  2013

5.  Spherical demons: fast diffeomorphic landmark-free surface registration.

Authors:  B T Thomas Yeo; Mert R Sabuncu; Tom Vercauteren; Nicholas Ayache; Bruce Fischl; Polina Golland
Journal:  IEEE Trans Med Imaging       Date:  2009-08-25       Impact factor: 10.048

6.  A surface-based technique for warping three-dimensional images of the brain.

Authors:  P Thompson; A W Toga
Journal:  IEEE Trans Med Imaging       Date:  1996       Impact factor: 10.048

7.  Automatic cortical sulcal parcellation based on surface principal direction flow field tracking.

Authors:  Gang Li; Lei Guo; Jingxin Nie; Tianming Liu
Journal:  Neuroimage       Date:  2009-03-25       Impact factor: 6.556

8.  Morphometry of anatomical shape complexes with dense deformations and sparse parameters.

Authors:  Stanley Durrleman; Marcel Prastawa; Nicolas Charon; Julie R Korenberg; Sarang Joshi; Guido Gerig; Alain Trouvé
Journal:  Neuroimage       Date:  2014-06-26       Impact factor: 6.556

  8 in total
  3 in total

1.  Predicting infant cortical surface development using a 4D varifold-based learning framework and local topography-based shape morphing.

Authors:  Islem Rekik; Gang Li; Weili Lin; Dinggang Shen
Journal:  Med Image Anal       Date:  2015-11-10       Impact factor: 8.545

2.  Multidirectional and Topography-based Dynamic-scale Varifold Representations with Application to Matching Developing Cortical Surfaces.

Authors:  Islem Rekik; Gang Li; Weili Lin; Dinggang Shen
Journal:  Neuroimage       Date:  2016-04-30       Impact factor: 6.556

3.  Joint prediction of longitudinal development of cortical surfaces and white matter fibers from neonatal MRI.

Authors:  Islem Rekik; Gang Li; Pew-Thian Yap; Geng Chen; Weili Lin; Dinggang Shen
Journal:  Neuroimage       Date:  2017-03-09       Impact factor: 6.556

  3 in total

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