Non-parametric Diffeomorphic Image Registration with the Demons Algorithm

By Tom Kamiel Magda Vercauteren, Xavier Pennec, Aymeric Perchant, Nicholas Ayache. International Conference on Medical Image Computing and Computer-Assisted Intervention, 2007

456 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/8813e0a8288224f4028c5e763e87bb66807eafc2

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In Aerospace Engineering

In Computer Vision and Pattern Recognition

Citations in the corpus

Deformable Medical Image Registration: A Survey (2013, methodology): “In [44], Vercauteren et al. proposed a variant of Thirion’s algorithm endowed with the diffeomorphic property.”
DRAMMS: Deformable Registration via Attribute Matching and Mutual-Saliency Weighting (2009, methodology): “Existing deformable registration methods can be generally classiﬁed into two main categories: voxel-wise methods (e.g., [1,2,3,4,5,6,7]) and landmark/feature-based methods (e.g., [8,9,10,11,12,13,14]).”
Diffeomorphic demons: Efficient non-parametric image registration (2009, methodology): “One of the main results of this theoretical analysis we initially presented in (Vercauteren et al., 2007a) is to show that the symmetric forces variant can be related to the ESM scheme of (Benhimane and Malis, 2004; Malis, 2004).”
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015 (2015, methodology): “For our implementation of Atlas-based segmentation methods, the registration algorithms dDemons [20] and FFD-MI [3] are used to propagate the segmentation mask of end-diastole image from all other subjects to the end-diastole image of the test subject, followed by a majority voting to obtain the fin”
Machine Learning and Radiology (2012, methodology): “Vercauteren et al. conducted research on nonparametric diffeomorphic image registration by adapting Thirion’s demons algorithm to the space of diffeomorphic transformations (Vercauteren et al., 2007).”
Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration (2009, methodology): “This non-parametric algorithm generalizes Thirion’s Demons algorithm (Thirion, 1998) to produce a diffeomorphic spatial transformation (Vercauteren et al., 2007).”
Medical image registration: a review (2014, methodology): “The Dice similarity coefﬁcient quantiﬁes the amount of overlapping regions and has also been used to assess the registration accuracy (Alterovitza et al. 2006; Vercauteren et al. 2007; Loeckx et al. 2010).”