Geodesic Shooting for Computational Anatomy

By Michael I. Miller, Alain Trouv'e, Laurent Younes. Journal of Mathematical Imaging and Vision, 2006

406 citations recorded by the source corpus.

Subfields: Computational Mechanics, Computer Vision and Pattern Recognition, Geometry and Topology

View Paper: https://www.semanticscholar.org/paper/37dbd33b1eb8c2e8414e2716e743248d2172637e

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Citations in the corpus

Brain templates and atlases (2012, neutral): “…et al., 2005; Christensen et al., 1997; Chung et al., 2001; Grenander and Miller, 2007; Guo et al., 2005; Lian and Davatzikos, 2011; Miller, 2004; Miller et al., 1993, 2002, 2006; Thompson and Toga, 1996, 1999; Thompson et al., 2000a,b; Wang et al., 2005; Yeo et al., 2010a; Yushkevich et al.,…”
Multi-Contrast Human Neonatal Brain Atlas: Application to Normal Neonate Development Analysis (2011, positive): “test the feasibility of the atlas-based analysis to detect the diffusion properties of the infant brain using the JHUneonate-SS and LDDMM, we measured FA and MD of 20 white matter structures and four deep gray structures of the 33 DTIs normalized to the JHU-neonate-SS.”
A Reproducible Evaluation of ANTs Similarity Metric Performance in Brain Image Registration (2010, background): “, 2001), functional (Miller et al., 2006), and population data (Avants et al.”
Shape deformation analysis from the optimal control viewpoint (2014, methodology): “This framework has led to the development of a family of registration algorithms called Large Deformation Diffeomorphic Metric Mapping (LDDMM), in which the correspondence between two shapes comes from the minimization of an objective functional defined as a sum of two terms [6, 7, 19, 22, 23].”
Occupancy Flow: 4D Reconstruction by Learning Particle Dynamics (2019, methodology): “Our approach to modeling time-varying geometry is re-lated to deformation ﬁeld-based methods [36, 43] which have a long-standing history in computer graphics [40,69].”
Surface Matching via Currents (2005, background): “It has been shown in [17] that the image of the template S under the flow φt is completely determined by the momentum ( α) at time t = 0.”
Diffeomorphic registration using geodesic shooting and Gauss–Newton optimisation (2011, neutral): “More complete explanations of the mathematics underlying the GS approach are to be found in the literature (Miller et al., 2006; Cotter and Holm, 2006; Marsland and McLachlan, 2007; Younes, 2007; Younes et al., 2008, 2009) or in various textbooks (Younes, 2010; Holm et al.”
Evolution of hippocampal shapes across the human lifespan (2013, background): “The initial momentum, similar to the concept in physics, uniquely determined the diffeomorphic flow deforming the atlas to individual hippocampi [Miller et al., 2006].”
INTRINSIC SHAPE ANALYSIS: GEODESIC PCA FOR RIEMANNIAN MANIFOLDS MODULO ISOMETRIC LIE GROUP ACTIONS (2007, methodology): “Such numerical methods have been proposed, e.g., by Miller, Trouvé, and Younes (2006) or Schmidt, Clausen and Cremers (2006), for general models, such as e.g., Michor and Mumford (2006) or Klassen et al. (2004), for closed 2D curves, or closed 2D and 3D contours based on medial axes, e.g., Pizer…”
A fast diffeomorphic image registration algorithm (2007, methodology): “Others have suggested a variable velocity framework for computational anatomy, whereby the analyses are based upon “ initial momentum ” maps (Miller et al., 2006; Vaillant et al., 2004).”
Symmetric Diffeomorphic Modeling of Longitudinal Structural MRI (2013, methodology): “Symmetric longitudinal registration v It is now reasonably well known that a diffeomorphism ( φ v ) may be computed from an initial velocity ﬁeld ( v ) using a procedure known as geodesic shooting (Miller et al., 2006).”