Spherical Demons: Fast Surface Registration

Yeo, B.T. Thomas; Sabuncu, Mert R.; Vercauteren, Tom; Ayache, Nicholas; Fischl, Bruce; Golland, Polina

doi:10.1007/978-3-540-85988-8_89

Cited by 41 publications

(38 citation statements)

References 24 publications

(60 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Nevertheless, the framework we proposed showed to be versatile enough to be extended to many types of images such as DTI (Yeo et al, 2008c), Cortical surfaces (Yeo et al, 2008b) or 4D time series of cardiac images (Peyrat et al, 2008). By borrowing some ideas from (Avants et al, 2008;Cachier et al, 2003;Hermosillo et al, 2002), other similarity criteria could also be used.…”

Section: Discussionmentioning

confidence: 99%

Diffeomorphic demons: Efficient non-parametric image registration

et al. 2009

Self Cite

View full text Add to dashboard Cite

We propose an efficient non-parametric diffeomorphic image registration algorithm based on Thirion's demons algorithm. In the first part of this paper, we show that Thirion's demons algorithm can be seen as an optimization procedure on the entire space of displacement fields. We provide strong theoretical roots to the different variants of Thirion's demons algorithm. This analysis predicts a theoretical advantage for the symmetric forces variant of the demons algorithm. We show on controlled experiments that this advantage is confirmed in practice and yields a faster convergence. In the second part of this paper, we adapt the optimization procedure underlying the demons algorithm to a space of diffeomorphic transformations. In contrast to many diffeomorphic registration algorithms, our solution is computationally efficient since in practice it only replaces an addition of displacement fields by a few compositions. Our experiments show that in addition to being diffeomorphic, our algorithm provides results that are similar to the ones from the demons algorithm but with transformations that are much smoother and closer to the gold standard, available in controlled experiments, in terms of Jacobians.

show abstract

Section: Discussionmentioning

confidence: 99%

Diffeomorphic demons: Efficient non-parametric image registration

et al. 2009

Self Cite

View full text Add to dashboard Cite

show abstract

“…provided by experts when available. In the future, comparisons with other recent methods, especially landmark-free approaches [16] and others that do not resort to point-to-point correspondences [17] will be led.…”

Section: Discussionmentioning

confidence: 99%

Setting Priors and Enforcing Constraints on Matches for Nonlinear Registration of Meshes

Combès

Prima

2009

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009

View full text Add to dashboard Cite

Abstract. We show that a simple probabilistic modelling of the registration problem for surfaces allows to solve it by using standard clustering techniques. In this framework, point-to-point correspondences are hypothesized between the two free-form surfaces, and we show how to specify priors and to enforce global constraints on these matches with only minor changes to the optimisation algorithm. The purpose of these two modifications is to increase its capture range and to obtain more realistic geometrical transformations between the surfaces. We conclude with some validation experiments and results on synthetic and real data.

show abstract

“…This is a particularly challenging task because of the brain convoluted geometry and the high interindividual variability (J.-F. Mangin et al 2004). Various registration approaches have been proposed, including intensity--based in the voxel space (Rueckert et al 1999), (T. Vercauteren et al 2007) or shape--based in a surface representation of the brain (Yeo et al 2008(Yeo et al , 2010, (Eckstein et al 2007). Although intensity--based non--rigid registration methods work well in intrasubject registration, cortical folds do not match well and may not effectively address the issues arising from the variability across a population (Hellier et al 2003).…”

Section: Introductionmentioning

confidence: 99%

“…The main issues are related with i) the preservation of gyri and sulci and with ii) the topology correction. Firstly, since the folding patterns correlate well with functional and anatomical regions between individuals (Fischl et al 2008) a reliable detection of gyri and sulci during the segmentation step is required. Various methods have been proposed: Hutton (Hutton et al 2008) used a layering method in the voxel space based on mathematical morphology to detect deep sulci.…”

Section: Introductionmentioning

confidence: 99%

“…Concerning the surface based non--rigid registration, some of the previously proposed approaches have used a parametric representation on a sphere, obtained either through iterative relaxation like in Freesurfer (B. Fischl, M. I Sereno, and A. M Dale 1999) or conformal mapping (Angenent et al 1999), (Gu et al 2004). In the spherical domain, the registration strategy relies on features such as sulcal landmarks or mean curvature, or convexity (Yeo et al 2010), (Yeo et al 2008) , (Ziolko et al 2006). In those approaches the global shape information is not explicit and the registration is dependent on the selected features.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Cortical surface mapping using topology correction, partial flattening and 3D shape context-based non-rigid registration for use in quantifying atrophy in Alzheimer's disease

Acosta

Fripp

Doré

et al. 2012

Journal of Neuroscience Methods

View full text Add to dashboard Cite

's diseaseMagnetic resonance (MR) provides a non--invasive way to investigate changes in the brain resulting from aging or neurodegenerative disorders such as Alzheimer's disease (AD). Performing accurate analysis for population studies is challenging because of the interindividual anatomical variability. A large set of tools are found to perform studies of brain anatomy and population analysis (FreeSurfer, SPM, FSL). In this paper we present a newly developed surface--based processing pipeline (milxCTE) that allows accurate vertex--wise statistical comparisons of brain modifications, such as cortical thickness (CTE). The brain is first segmented into the three main tissues: white matter, gray matter and cerebrospinal fluid, after CTE is computed, a topology corrected mesh is generated. Partial inflation and non--rigid registration of cortical surfaces to a common space using shape context are then performed. Each of the steps was firstly validated using MR images from the OASIS database. We then applied the pipeline to a sample of individuals randomly selected from the AIBL study on AD and compared with FreeSurfer. For a population of 50 individuals we found correlation of cortical thickness in all the regions of the brain (average r =0.62 left and r =0.64 right hemispheres). We finally computed changes in atrophy in 32 AD patients and 81 healthy elderly individuals. Significant 2 differences were found in regions known to be affected in AD. We demonstrated the validity of the method for use in clinical studies which provides an alternative to well established techniques to compare different imaging biomarkers for the study of neurodegenerative diseases.

show abstract

Spherical Demons: Fast Surface Registration

Cited by 41 publications

References 24 publications

Diffeomorphic demons: Efficient non-parametric image registration

Diffeomorphic demons: Efficient non-parametric image registration

Setting Priors and Enforcing Constraints on Matches for Nonlinear Registration of Meshes

Cortical surface mapping using topology correction, partial flattening and 3D shape context-based non-rigid registration for use in quantifying atrophy in Alzheimer's disease

Contact Info

Product

Resources

About