The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Variational problems on flows of diffeomorphisms for image matching
Open accessAbstract
This paper studies a variational formulation of the image matching problem. We consider a scenario in which a canonical representative image T is to be carried via a smooth change of variable into an image that is intended to provide a good fit to the observed data. The images are all defined on an open bounded set G ⊂ R 3 . The changes of variable are determined as solutions of the nonlinear Eulerian transport equation \[ d η ( s ; x ) d s = v ( η ( s ; x ) , s ) , η ( τ ; x ) = x , ( 0.1 ) \] with the location η ( 0 ; x ) in the canonical image carried to the location x in the deformed image. The variational problem then takes the form \[ arg min v [ ‖ v ‖ 2 + ∫ G | T o η ( 0 ; x ) − D ( x ) | 2 d x ] , ( 0.2 ) \] where ‖ v ‖ is an appropriate norm on the velocity field v ( ⋅ , ⋅ ) , and the second term attempts to enforce fidelity to the data.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“This is unsurprising as, similar to existing optical flow approaches [14, 15], directly predicting displacements does not encode deformation smoothness.”
From Quicksilver: Fast predictive image registration – A deep learning approach (2017) · cites this paper as [15]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Timoshenko, S. P., & Goodier, J. N. (1934) · Virtual Defense Library (Ministerio de Defensa) · Cited by 13,717
Ordinary Differential Equations
Stewart, J. M. (2017) · Cambridge University Press eBooks · doi:10.1017/9781108120241.010 · Cited by 7,299
Weakly Differentiable Functions
Ziemer, W. P. (1989) · Graduate texts in mathematics · doi:10.1007/978-1-4612-1015-3 · Cited by 2,225
Deformable templates using large deformation kinematics
Christensen, G. E., Rabbitt, R. D., & Miller, M. I. (1996) · IEEE Transactions on Image Processing · doi:10.1109/83.536892 · Cited by 1,146
Self-citationMultiresolution elastic matching
Bajcsy, R., & Kovačič, S. (1989) · Computer Vision Graphics and Image Processing · doi:10.1016/s0734-189x(89)80014-3 · Cited by 1,118
Stochastic Flows and Stochastic Differential Equations
MTW, & Kunita, H. (1998) · Journal of the American Statistical Association · doi:10.2307/2669903 · Cited by 1,014
Representations of Knowledge in Complex Systems
Grenander, U., & Miller, M. I. (1994) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.2517-6161.1994.tb02000.x · Cited by 619
Self-citationMathematical textbook of deformable neuroanatomies.
Miller, M. I., Christensen, G. E., Amit, Y., & Grenander, U. (1993) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.90.24.11944 · Cited by 464
Self-citation3D brain mapping using a deformable neuroanatomy
Christensen, G. E., Rabbitt, R. D., & Miller, M. I. (1994) · Physics in Medicine and Biology · doi:10.1088/0031-9155/39/3/022 · Cited by 358
Self-citationStructural Image Restoration through Deformable Templates
Amit, Y., Grenander, U., & Piccioni, M. (1991) · Journal of the American Statistical Association · doi:10.1080/01621459.1991.10475053 · Cited by 325
Self-citation
Research works printed but not linked: 3
- Christensen, Gary Edward, 1994, Deformable shape models for anatomy
- G. E. Christensen, R. D. Rabbitt, and M. I. Miller, A deformable neuroanatomy textbook based on viscous fluid mechanics, In Jerry Prince and Thordur Runolfsson, editors, Proceedings of the Twenty-Seventh Annual Conference on Information Sciences and Systems, pp. 211–216, Baltimore, Maryland, March 24-26, 1993. Department of Electrical Engineering, The Johns Hopkins University.
- Hijab, Omar Bakri, 1980, MINIMUM ENERGY ESTIMATION
Cited by
Sorted by citations
Items 301–400 of 447
Bézier curves in the space of imagesPreprint
Effland, A., Rumpf, M., Simon, S., Stahn, K., & Wirth, B. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1503.02527 · Cited by 6
A Statistical Pipeline for Identifying Physical Features that Differentiate Classes of 3D ShapesPreprint
Wang, B., Sudijono, T., Kirveslahti, H., Gao, T., Boyer, D. M., Mukherjee, S., & Crawford, L. A. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/701391 · Cited by 6
Ye, M., Yang, D., Kanski, M., Axel, L., & Metaxas, D. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.01310 · Cited by 5
SRIF: Semantic Shape Registration Empowered by Diffusion-based Image Morphing and Flow Estimation
Sun, M., Guo, C., Jiang, P., Mao, S., Chen, Y., & Huang, R. (2024) · SIGGRAPH Asia Conference Papers · doi:10.1145/3680528.3687567 · Cited by 9
A Novel Few-Shot Learning Framework for Supervised Diffeomorphic Image Registration Network
Chen, K., Han, H., Wei, J., & Zhang, Y. (2025) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2025.3585199 · Cited by 5
A Geodesic Landmark Shooting Algorithm for Template Matching and Its Applications
Camassa, R., Kuang, D., & Lee, L. (2017) · SIAM Journal on Imaging Sciences · doi:10.1137/15m104373x · Cited by 5
Numerical method for image registration model based on optimal mass transport
Chen, Y., & Wan, J. W. L. (2018) · Inverse Problems and Imaging · doi:10.3934/ipi.2018018 · Cited by 5
Shape Spaces: From Geometry to Biological Plausibility
Charon, N., & Laurent Younes, B. (2023) · Springer eBooks · doi:10.1007/978-3-030-98661-2_118 · Cited by 5
Li, Y., Chen, K., Chen, C., & Zhang, J. (2024) · Applied Mathematical Modelling · doi:10.1016/j.apm.2024.02.033 · Cited by 5
Zhang, Z., Sahn, D. J., & Song, X. B. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-28326-0_28 · Cited by 5
Flexible Shape Matching with Finite Element Based LDDMM
Günther, A., Lamecker, H., & Weiser, M. (2012) · International Journal of Computer Vision · doi:10.1007/s11263-012-0599-3 · Cited by 5
Computing metrics on anatomical shapes in computational anatomy
Beg, M. F., Miller, M. I., Trouvé, A., & Laurent Younes, B. (2002) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.2002.1106240 · Cited by 5
Self-citationTime multiscale regularization for nonlinear image registration
Bao, L., Chen, K., Kong, D., Ying, S., & Zeng, T. (2024) · Computerized Medical Imaging and Graphics · doi:10.1016/j.compmedimag.2024.102331 · Cited by 4
A Sheaf-Theoretic Construction of Shape Space
Arya, S., Curry, J. M., & Mukherjee, S. (2024) · Foundations of Computational Mathematics · doi:10.1007/s10208-024-09650-1 · Cited by 4
Metric-Based Pairwise and Multiple Image Registration
Xie, Q., Kurtek, S., Klassen, E. P., Christensen, G. E., & Srivastava, A. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-10605-2_16 · Cited by 4
The Abstract Setting for Shape Deformation Analysis and LDDMM Methods
Arguillère, S. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-25040-3_18 · Cited by 4
Signal Classification in Quotient Spaces via Globally Optimal Variational Calculus
Chirikjian, G. S. (2017) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw.2017.103 · Cited by 4
Chevallier, J., Debavelaere, V., & Allassonnière, S. (2021) · SIAM Journal on Imaging Sciences · doi:10.1137/20m1328026 · Cited by 4
Multiscale Frame-Based Kernels for Large Deformation Diffeomorphic Metric Mapping
Tan, M., & Qiu, A. (2018) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2018.2832038 · Cited by 4
Landmark-based algorithms for group average and pattern recognition
Huzurbazar, S. V., Kuang, D., & Lee, L. (2018) · Pattern Recognition · doi:10.1016/j.patcog.2018.09.002 · Cited by 4
Diffeomorphic Shape Matching by Operator Splitting in 3D Cardiology Imaging
Zhang, P., Mang, A., He, J., Azencott, R., El-Tallawi, K. C., & Zoghbi, W. A. (2021) · Journal of Optimization Theory and Applications · doi:10.1007/s10957-020-01789-5 · Cited by 4
Template-Based Image Reconstruction Facing Different Topologies
Neumayer, S., & Topalović, A. (2024) · Journal of Scientific Computing · doi:10.1007/s10915-023-02446-5 · Cited by 4
Han, H., & Wang, Z. (2019) · Applied Mathematics and Computation · doi:10.1016/j.amc.2019.03.024 · Cited by 4
Bézier Curves in the Space of Images
Effland, A., Rumpf, M., Simon, S., Stahn, K., & Wirth, B. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-18461-6_30 · Cited by 4
Yang, D., Li, H., Low, D. A., Deasy, J. O., & Naqa, I. E. (2008) · Asilomar Conference on Signals, Systems and Computers (ACSSC) · doi:10.1109/acssc.2008.5074766 · Cited by 4
Direct LDDMM of Discrete Currents with Adaptive Finite Elements
Günther, A., Lamecker, H., & Weiser, M. (2011) · Cited by 4
Diffeomorphic Cardiac Motion Estimation with Anisotropic Regularization along Myofiber Orientation
Zhang, Z., Sahn, D. J., & Song, X. B. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-31340-0_21 · Cited by 5
Variational Methods in Shape Analysis
Rumpf, M., & Wirth, B. (2010) · Springer eBooks · doi:10.1007/978-0-387-92920-0_31 · Cited by 4
Medical image analysis via frechet means of diffeomorphisms
Joshi, S. C., & Davis, B. C. (2008) · Cited by 4
From model based to learned regularization in medical image registration: A comprehensive review
Reithmeir, A., Spieker, V., Sideri‐Lampretsa, V., Rueckert, D., Schnabel, J. A., & Zimmer, V. A. (2025) · Medical Image Analysis · doi:10.1016/j.media.2025.103854 · Cited by 3
Sparsity and scale: Compact representations of deformation for diffeomorphic registration
Sommer, S., Nielsen, M., & Pennec, X. (2012) · IEEE Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA) · doi:10.1109/mmbia.2012.6164753 · Cited by 3
Planar curve registration using Bayesian inversion
Bock, A., Cotter, C. J., & Kirby, R. C. (2024) · Computers & Mathematics with Applications · doi:10.1016/j.camwa.2024.02.005 · Cited by 3
Invertible nonlinear cluster unwrapping
Shaker, M., Myhre, J. N., Kaba, M. D., & Deniz Erdogmus, B. (2014) · Machine learning for signal processing ... · doi:10.1109/mlsp.2014.6958878 · Cited by 3
A Shape Median Based on Symmetric Area Differences
Berkels, B., Linkmann, G., & Rumpf, M. (2008) · Cited by 3
Diffeomorphic Image Matching with Left-Invariant Metrics
Schmah, T., Risser, L., & Vialard, F. (2015) · Fields Institute communications · doi:10.1007/978-1-4939-2441-7_16 · Cited by 3
Diffeomorphic Upsampling of Serially Acquired Sparse 2D Cross-Sections in Cardiac MRI
Lee, B. C., Tward, D. J., Wei, J., Tipre, D. N., Weiss, R. G., Miller, M. I., & Ardekani, S. (2019) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2019.8856317 · Cited by 3
Self-citationBayesian Multiple Atlas Deformable Templates
Miller, M. I., Mori, S., Tang, X., Tward, D. J., & Zhang, Y. (2015) · Elsevier eBooks · doi:10.1016/b978-0-12-397025-1.00312-2 · Cited by 3
Self-citationDiffeomorphic shape evolution coupled with a reaction-diffusion PDE on a growth potential
Hsieh, D.-N., Arguillère, S., Charon, N., & Laurent Younes, B. (2021) · Quarterly of Applied Mathematics · doi:10.1090/qam/1600 · Cited by 3
Shape deformation and optimal control
Arguillère, S., Trélat, E., Trouvé, A., & Laurent Younes, B. (2014) · ESAIM Proceedings and Surveys · doi:10.1051/proc/201445031 · Cited by 3
Infinitesimal Drift Diffeomorphometry Models for Population Shape Analysis
Lee, B. C., Tward, D. J., Hu, Z., Trouvé, A., & Miller, M. I. (2020) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw50498.2020.00439 · Cited by 3
Self-citationLarge Deformation Diffeomorphic Registration Using Fine and Coarse Strategies
Risser, L., Vialard, F., Deprez, M., Holm, D. D., & Rueckert, D. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-14366-3_17 · Cited by 3
A second order variational approach for diffeomorphic matching of 3D surfaces
Yue, Q. (2013) · Cited by 3
Higher Order Kernels and Locally Affine LDDMM RegistrationPreprint
Sommer, S., Nielsen, M., Darkner, S., & Xavier Pennec, B. (2011) · arXiv (Cornell University) · Cited by 3
Least action principles for incompressible flows and optimal transport between shapesPreprint
Liu, J., Pego, R. L., & Slepčev, D. (2016) · arXiv (Cornell University) · Cited by 3
Automating Whole Brain Histology to MRI Registration: Implementation of a Computational PipelinePreprint
Alegro, M., Alho, E. J. L., Martin, M. D. G. M., Grinberg, L. T., Heinsen, H., Lopes, R. D. D., Amaro-Jr, E., & Zöllei, L. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1905.09339 · Cited by 4
Variational time discretization of geodesic calculusPreprint
Rumpf, M., & Wirth, B. (2012) · arXiv (Cornell University) · doi:10.48550/arxiv.1210.2097 · Cited by 3
Bayesian Unsupervised Disentanglement of Anatomy and Geometry for Deep Groupwise Image Registration
Luo, X., Wang, X., Shapiro, L. G., Yuan, C., Feng, J., & Zhuang, X. (2025) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2025.3609521 · Cited by 2
Bayesian Atlas Estimation from High Angular Resolution Diffusion Imaging (HARDI)
Du, J., Goh, A., & Qiu, A. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-40020-9_15 · Cited by 2
Shape Spaces: From Geometry to Biological Plausibility
Charon, N., & Laurent Younes, B. (2022) · Springer eBooks · doi:10.1007/978-3-030-03009-4_118-1 · Cited by 2
Mang, A., He, J., & Azencott, R. (2023) · Journal of Computational Physics · doi:10.1016/j.jcp.2023.112463 · Cited by 2
CLAIRE: Scalable GPU-Accelerated Algorithms for Diffeomorphic Image Registration in 3D
Mang, A. (2024) · Applied and numerical harmonic analysis · doi:10.1007/978-3-031-66497-7_8 · Cited by 2
Computational Motion Phantoms and Statistical Models of Respiratory Motion
Ehrhardt, J., Klinder, T., & Lorenz, C. D. (2013) · Biological and medical physics series · doi:10.1007/978-3-642-36441-9_10 · Cited by 2
Nonrigid Medical Image Registration Based on Mesh Deformation Constraints
Lin, X., Ruan, S., Qiu, T., & Guo, D. (2013) · Computational and Mathematical Methods in Medicine · doi:10.1155/2013/373082 · Cited by 2
Arguillère, S. (2015) · SIAM Journal on Matrix Analysis and Applications · doi:10.1137/130926584 · Cited by 2
Kernel principal component analysis of the ear morphology
Zolfaghari, R., Épain, N., Jin, C. T., Glaunès, J., & Tew, A. I. (2017) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2017.7952202 · Cited by 2
Frame to Frame Diffeomorphic Motion Analysis from Echocardiographic Sequences
Zhang, Z., Sahn, D. J., & Song, X. B. (2011) · Cited by 2
Learning landmark geodesics using the ensemble Kalman filter
Bock, A., & Cotter, C. J. (2021) · Foundations of Data Science · doi:10.3934/fods.2021020 · Cited by 2
Shape analysis via gradient flows on diffeomorphism groups
Balehowsky, T., Karlsson, C.-J., & Modin, K. (2022) · Nonlinearity · doi:10.1088/1361-6544/aca73c · Cited by 2
Representations for Functional of Hilbert Space Valued Diffusions
Budhiraja, A. S., & Dupuis, P. G. (1999) · Birkhäuser Boston eBooks · doi:10.1007/978-1-4612-1784-8_1 · Cited by 2
Self-citationTime Discrete Geodesics in Deep Feature Spaces for Image Morphing
Effland, A., Kobler, E., Pock, T., & Rumpf, M. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-22368-7_14 · Cited by 2
Metamorphic Image Registration Using a Semi-lagrangian Scheme
François, A., Gori, P., & Glaunès, J. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-80209-7_84 · Cited by 2
Provenzi, E. (2018) · MDPI eBooks · doi:10.3390/books978-3-03842-958-6 · Cited by 2
Neuroimaging Alzheimer's disease
Toga, A. W., Mega, M. S., & Thompson, P. M. (2004) · Cambridge University Press eBooks · doi:10.1017/cbo9780511526886.009 · Cited by 2
Yang, H., Lyu, J., Cheng, P., & Tang, X. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2108.00690 · Cited by 2
Projective LDDMM: Mapping Molecular Digital Pathology with Tissue MRIPreprint
Stouffer, K. M., Witter, M. P., Tward, D. J., & Miller, M. I. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.04.22.489163 · Cited by 2
Self-citationThe general setting for Shape AnalysisPreprint
Arguillère, S. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1504.01767 · Cited by 2
Zapf, B., Haubner, J., Baumgärtner, L., & Schmidt, S. (2025) · SIAM Journal on Scientific Computing · doi:10.1137/23m1570727 · Cited by 1
Collision Constraints and Diffeomorphisms: Dealing With Physics in Deformable Image Registration
Alscher, T., Petersen, J., Lauze, F., Erleben, K., & Darkner, S. (2025) · IEEE Access · doi:10.1109/access.2025.3588760 · Cited by 1
Tward, D. J., Gray, B., Li, X., Huo, B., Banerjee, S., Savoia, S., Mezias, C., Das, S., Miller, M. I., & Mitra, P. P. (2025) · Nature Communications · doi:10.1038/s41467-025-65317-7 · Cited by 1
Self-citationStationary Velocity Fields on Matrix Groups for Deformable Image Registration
Bostelmann, J., Gildemeister, O., & Lellmann, J. (2026) · Journal of Mathematical Imaging and Vision · doi:10.1007/s10851-026-01284-y · Cited by 1
Romor, F., Galarce, F., Brüning, J., Goubergrits, L., & Caiazzo, A. (2026) · SIAM Journal on Imaging Sciences · doi:10.1137/25m1741820 · Cited by 1
Reduction by Lie Group Symmetries in Diffeomorphic Image Registration and Deformation Modelling
Sommer, S., & Jacobs, H. O. (2015) · Symmetry · doi:10.3390/sym7020599 · Cited by 1
Analysis of the geodesic interpolating spline
Mills, A., & Shardlow, T. (2008) · European Journal of Applied Mathematics · doi:10.1017/s0956792508007493 · Cited by 1
Symmetric Data Attachment Terms for Large
Beg, M. F., & KHAN, A. R. (2007) · Cited by 1
Small noise large deviations for infinite dimensional stochastic dynamical systems
Maroulas, V. (2019) · Carolina Digital Repository (University of North Carolina at Chapel Hill) · doi:10.17615/s679-ba11 · Cited by 1
Performance of Image Matching in the Computational Anatomy Gateway
Tward, D. J., Lee, B., Mitra, P. P., & Miller, M. I. (2017) · Practice and Experience in Advanced Research Computing · doi:10.1145/3093338.3093361 · Cited by 1
Self-citationConstrained Linear Curvature Image Registration Model and Its Numerical Algorithm
Zhang, J. (2020) · Mathematical Problems in Engineering · doi:10.1155/2020/9468215 · Cited by 1
Becker, F., Petrab, S., & Schnörr, C. (2014) · Springer eBooks · doi:10.1007/978-3-642-27795-5_38-3 · Cited by 1
Consistent Approximation of Interpolating Splines in Image Metamorphosis
Justiniano, J., Rajković, M., & Rumpf, M. (2022) · Journal of Mathematical Imaging and Vision · doi:10.1007/s10851-022-01128-5 · Cited by 1
Time Discrete Extrapolation in a Riemannian Space of Images
Effland, A., Rumpf, M., & Schäfer, F. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-58771-4_38 · Cited by 1
Splines for Image Metamorphosis
Justiniano, J., Rajković, M., & Rumpf, M. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-75549-2_37 · Cited by 1
2 D ‐to‐3 D Face Recognition Systems
Miller, M. I., Vaillant, M., Hoffman, W., & Schuepp, P. (2008) · Wiley Handbook of Science and Technology for Homeland Security · doi:10.1002/9780470087923.hhs532 · Cited by 1
Self-citationBayesian Estimation of White Matter Atlas from High Angular Resolution Diffusion ImagingPreprint
Du, J., Goh, A., & Qiu, A. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1310.3233 · Cited by 1
Discrete geodesic calculus in the space of viscous fluidic objectsPreprint
Rumpf, M., & Wirth, B. (2012) · arXiv.org · doi:10.48550/arxiv.1210.0822 · Cited by 3
Computational Anatomy for Generating 3D Avatars and Boosting Face Recognition Systems
Vaillant, M., Zang, G., Aliperti, J., Santhanam, N., Doucette, S. P., Hoffman, B., & Miller, M. I. (2006) · 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops · doi:10.1109/cvpr.2005.571 · Cited by 1
Self-citationControlling the deformation map in diffeomorphic image registration.Preprint
Mang, A., & Biros, G. (2015) · arXiv (Cornell University) · Cited by 1
Avants, B., Hurt, H., Giannetta, J. M., Epstein, C. L., Shera, D. M., Wang, J., & Gee, J. C. (2006) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw.2006.30 · Cited by 1
Diffeomorphic point matching with applications in medical image analysis
Guo, H., & Rangarajan, A. (2005) · Cited by 1
Sulman, M. H. M. (2003) · Summit (Simon Fraser University) · Cited by 1
EM-LDDMM for 3D to 2D registrationPreprint
Tward, D. J., & Miller, M. I. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/604405 · Cited by 1
Self-citationArguillère, S. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1306.6255 · Cited by 1
Stouffer, K. M., Trouvé, A., Laurent Younes, B., Kunst, M., Ng, L., Zeng, H., Anant, M. M.-G., Fan, J., Kim, Y., & Miller, M. I. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.03.28.534622 · Cited by 1
Self-citationA Non-Euclidean Metric for the Classification of Variations in Medical Images
Twining, C., & Marsland, S. (2003)
Non-rigid Shape Comparison of Implicitly-Defined Curves
Thiruvenkadam, S. R., Groisser, D., & Chen, Y. (2005) · Lecture notes in computer science · doi:10.1007/11567646_19
Groupwise and Local Analysis of Image Warps
Twining, C., & Marsland, S. (2003)
Minimal distortion morphs generated by time-dependent vector fields
Bihun, O., Chicone, C. C., & Harris, S. G. (2009) · Journal of Mathematical Analysis and Applications · doi:10.1016/j.jmaa.2009.11.047
Zhang, Z., Sahn, D. J., & Song, X. B. (2012) · 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops · doi:10.1109/cvprw.2012.6239252
Diffeomorphic cortical surface mapping and its comparison with spherical cortical mapping
zhong, J., & Qiu, A. (2011) · ICME International Conference on Complex Medical Engineering (CME) · doi:10.1109/iccme.2011.5876807
Atlas based segmentation by diffeomorphic deformation
Cao, Y. (2008) · International Conference on Wavelet Analysis and Pattern Recognition · doi:10.1109/icwapr.2008.4635761
Integrative diffeomorphic metric mapping based on image and unlabeled points
Du, J., & Qiu, A. (2011) · ICME International Conference on Complex Medical Engineering (CME) · doi:10.1109/iccme.2011.5876809
Metadata
- Authors
- Dupuis, P., Grenander, U., & Miller, M. I.
- Affiliations
- Washington University in St. Louis (US)
- ORCID
- Miller, Michael I.
- Venue
- Quarterly of Applied Mathematics
- Publisher
- American Mathematical Society (AMS)
- Published
- 1998-09
- Volume
- 56
- Issue
- 3
- Pages
- 587-600
- ISSN
- 0033-569X (ISSN-L)
- 1552-4485
- OpenAlex
- W1507084921
- Cited by
- 447
- References
- 16
- Citations by year
- 2026: 7 · 2025: 13 · 2024: 12 · 2023: 10 · 2022: 10 · 2021: 19 · 2020: 22 · 2019: 22 · 2018: 21 · 2017: 26 · 2016: 15 · 2015: 32 · 2014: 20 · 2013: 19 · 2012: 25
- FWCI
- 5.67
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Quarterly of Applied Mathematics (publishedVersion)
- Funders
- National Science Foundation (9403820, 9424264)
- Brown University
- National Institutes of Health (R01-MH525158-01A1)
- Advanced Research Projects Agency
- Office of Naval Research (N00014)
- Army Research Office
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Physical Sciences › Mathematics › Applied Mathematics › Geometric Analysis and Curvature Flows
- Physical Sciences › Engineering › Computational Mechanics › Advanced Numerical Methods in Computational Mathematics
- Keywords
- image matching, variational problems, nonlinear transport, optimal control, image registration, 3D image data
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
