The DOI matches its Crossref record; 69 of the 71 references it cites were found in a registry or an index.
Variational Methods for Multimodal Image Matching
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
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
“General approaches address multimodal image registration by either performing image synthesis [22, 23] to change the problem to a uni-modal image registration task, or by proposing complex, hand-crafted [24, 25, 26, 27] or learned [28, 29, 30, 31, 32] multi-modal image similarity measures.”
From Quicksilver: Fast predictive image registration – A deep learning approach (2017) · cites this paper as [28]
Citations
Cites
Partial Differential Equations
Chern, S.-S. (1988) · Lecture notes in mathematics · doi:10.1007/bfb0082920 · Cited by 23,546
Scale-space and edge detection using anisotropic diffusion
Perona, P., & Malik, J. (1990) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.56205 · Cited by 12,143
(1981) · Cited by 11,963
Mean shift: a robust approach toward feature space analysis
Comaniciu, D., & Meer, P. (2002) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.1000236 · Cited by 11,523
On Estimation of a Probability Density Function and Mode
Parzen, E. (1962) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177704472 · Cited by 10,831
Horn, B. K. P., & Schunck, B. G. (1981) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.965761 · Cited by 7,443
Multimodality image registration by maximization of mutual information
Maes, F., Collignon, A., Vandermeulen, D., Marchal, G., & Suetens, P. (1997) · IEEE Transactions on Medical Imaging · doi:10.1109/42.563664 · Cited by 4,547
Medical image analysis: progress over two decades and the challenges ahead
Duncan, J. S., & Ayache, N. (2000) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.824822 · Cited by 4,167
Three-dimensional computer vision: a geometric viewpoint
(1994) · Choice Reviews Online · doi:10.5860/choice.32-0357 · Cited by 3,032
Alignment by Maximization of Mutual Information
Viola, P. A., & Wells, W. M. (1997) · International Journal of Computer Vision · doi:10.1023/a:1007958904918 · Cited by 2,610
Research works printed but not linked: 3
- Christensen, G., Miller, M., and Vannier, M. 1994. A 3d deformable magnetic resonance textbook based on elasticity. In Proceedings of the American Association for Artificial Intelligence, Symposium: Applications of Computer Vision in Medical Image Processing.
- Hata, N., Dohi, T., Warfield, S.,, Kikinis, R., and Jolesz, F.A. 1998. Multi-modality deformable regristration of pre-and intra-operative images for mri-guided brain surgery. In First International Conference on Medical Image Computing and Computer-Assisted Intervention. G. Goos and J. Hartmanis (Eds.), vol. 1496 of Lecture Notes in Computer Science. Springer: Berlin.
- Toga, A., (Ed.). 1998. Brain Warping. Academic Press.
Cited by
Sorted by citations
Items 301–388 of 388
XeMRI to CT Lung Image Registration Enhanced with Personalized 4DCT-Derived Motion Model
Szmul, A., Matin, T., Gleeson, F. V., Schnabel, J. A., Grau, V., & Papież, B. W. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-00946-5_26 · Cited by 3
Fast variational alignment of non-flat 1D displacements for applications in neuroimaging
Flotho, P., Thinnes, D., Kühn, B., Roome, C. J., Vibell, J. F., & Strauß, D. J. (2021) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2021.109076 · Cited by 3
Hofmann, M., Schölkopf, B., Bezrukov, I., Cahill, N. D., Wells, Joshi, S. C., & Pohl, K. M. (2009) · MPG.PuRe (Max Planck Society) · Cited by 3
1082 Free-breathing single-shot DENSE myocardial strain imaging using deformable registration
Le, Y., Kellman, P., Bennett, E. E., Lin, A., Chefd’hotel, C., Lorenz, C. H., & Wen, H. (2008) · Journal of Cardiovascular Magnetic Resonance · doi:10.1186/1532-429x-10-s1-a207 · Cited by 3
Self-citationHahn, D. A., Daum, V., Joachim Hornegger, A., Bautz, W. A., & Kuwert, T. (2007) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2007.4437074 · Cited by 3
RIVAGe Feedback during Visual Integration : towards a Generic Architecture
Bullier, J., Rachid Deriche, B., Faugeras, O. D., Girard, P., Kornprobst, P., Papadopoulo, T., Viéville, T., Thorpe, S. J., Fize, D., & Guyonneau, R. (2004) · HAL · Cited by 3
Self-citationAccuracy Evaluation for Region Centroid-Based Registration of Fluorescent CLSM Imagery
Lee, S., Bajcsy, P., Lin, A., & Folberg, R. (2006) · EURASIP Journal on Advances in Signal Processing · doi:10.1155/asp/2006/82480 · Cited by 3
Hafner, D., Demetz, O., Weickert, J., & Reißel, M. (2014) · Journal of Mathematical Imaging and Vision · doi:10.1007/s10851-014-0529-9 · Cited by 2
Estimation of the blurring kernel in experimental HR-pQCT images based on mutual information
Li, Y., Sixou, B., & Peyrin, F. (2017) · European Signal Processing Conference (EUSIPCO) · doi:10.23919/eusipco.2017.8081577 · Cited by 2
Information-Theoretic Registration with Explicit Reorientation of Diffusion-Weighted Images
Jensen, H. G., Lauze, F., & Darkner, S. (2021) · Journal of Mathematical Imaging and Vision · doi:10.1007/s10851-021-01050-2 · Cited by 2
A Variational Model for Deformable Registration of Uni-modal Medical Images with Intensity Biases
Nie, Z., Li, C., Liu, H., & Yang, X. (2021) · Journal of Mathematical Imaging and Vision · doi:10.1007/s10851-021-01042-2 · Cited by 2
A statistical similarity measure for non-rigid multi-modal image registration
Shi, J.-L., Chen, Y., Rao, M., & Lee, J. (2010) · Medical Imaging · doi:10.1117/12.844553 · Cited by 4
On stochastic gradient descent and quadratic mutual information for image registration
Singh, A., & Ahuja, N. (2013) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2013.6738273 · Cited by 2
Automatic parameter regulation for CT/MRA viscous fluid registration
Tokuhisa, S., & Kaneko, K. (2010) · IEEE Region 10 Conference (TENCON) · doi:10.1109/tencon.2010.5685991 · Cited by 2
Fully automated mosaicking of pushbroom aerial imagery
Cariou, C., & Chehdi, K. (2008) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2008.4517807 · Cited by 2
Zikic, D., Kamen, A., & Navab, N. (2010) · Cited by 2
Most Likely Separation of Intensity and Warping Effects in Image Registration
Kühnel, L., Sommer, S., Pai, A., & Rakêt, L. L. (2017) · SIAM Journal on Imaging Sciences · doi:10.1137/16m1070980 · Cited by 2
The impact of matching functional on atrophy measurement from geodesic shooting in diffeomorphisms
Fleishman, G. M., & Thompson, P. M. (2017) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2017.7950655 · Cited by 2
Resolution Conversion of Volumetric Array Data for Multimodal Medical Image Analysis
Hosoya, K., Nozawa, K., & Imiya, A. (2020) · Communications in computer and information science · doi:10.1007/978-981-15-3651-9_16 · Cited by 2
Vargas-Bedoya, E., Rivera, J. C., Puerta-Yepes, M. E., Angulo, A., Wahl, N., & Cabal, G. (2022) · Applied Sciences · doi:10.3390/app12178523 · Cited by 2
Mathematical Properties of Pyramid-Transform-Based Resolution Conversion and Its Applications
Hosoya, K., Nozawa, K., Itoh, H., & Imiya, A. (2023) · Journal of Mathematical Imaging and Vision · doi:10.1007/s10851-023-01166-7 · Cited by 2
An Improved Convolutional Neural Network for 3D Unsupervised Medical Image Registration
Cai, G., Wang, J., & Chi, Z. (2020) · IEEE International Conference on Computer and Communications (ICCC) · doi:10.1109/iccc51575.2020.9344977 · Cited by 2
On complex-stepped Runge-Kutta methods for exact time integration of linear PDEs
Filatov, D. M. (2007) · Cited by 2
Supporting registration decisions during 3D medical volume reconstructions
Bajcsy, P., Lee, S., & Clutter, D. (2006) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.653854 · Cited by 2
Mutual information driven Inverse Consistent nonlinear registration
Tao, G., He, R., Datta, S., & Narayana, P. A. (2008) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.2008.4650076 · Cited by 2
Modelling Non-Rigid Dynamic Scenes from Multi-View Image Sequences
Pons, J.-P., Keriven, R., & Faugeras, O. D. (2005) · Springer eBooks · doi:10.1007/0-387-28831-7_27 · Cited by 2
Self-citationDeininger, K., Korf, P., Lauber, L., Grimm, R., Strecker, R., Steinacker, J., Lisson, C. S., Mühling, B., Schmidtke-Schrezenmeier, G., Rasche, V., et al. (2024) · Diagnostics · doi:10.3390/diagnostics14161787 · Cited by 1
Mai, D., Kara, D., Liu, Y., Moura, T. R. S., Sadıghı, M., Kanj, F., Wexler, E., Sosnovik, D. E., Hanna, M. A., Santangeli, P., et al. (2025) · Magnetic Resonance in Medicine · doi:10.1002/mrm.70181 · Cited by 1
Mathematical methods in biomedical imaging
Burger, M., Jan Modersitzki, C., & Tenbrinck, D. (2014) · GAMM-Mitteilungen · doi:10.1002/gamm.201410008 · Cited by 1
Intensity-Based Registration for Lung Motion Estimation
Cao, K., Ding, K., Amelon, R. E., Du, K., Reinhardt, J. M., Raghavan, M. L., & Christensen, G. E. (2013) · Biological and medical physics series · doi:10.1007/978-3-642-36441-9_7 · Cited by 1
Multi-scale Adaptive Mask 3D Rigid Registration of Ultrasound and CT Images
Zhijun, Z., Jerome, S., Soo, M. K., Yan, B., & Yeung, C. K. (2007) · British Machine Vision Conference (BMVC) · doi:10.5244/c.21.91 · Cited by 1
Symmetric multi-scale image registration
Mohagheghian, F., Ahmadian, A., Saberi, H., & Alirezaie, J. (2010) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.2010.5627551 · Cited by 1
Hu, S., Shao, P., Hui-fen, J., & Zhang, W. (2013) · Optik · doi:10.1016/j.ijleo.2013.07.123 · Cited by 1
FAST, MULTI-MODAL AND DISCONTINUITY-PRESERVING IMAGE REGISTRATION USING MUTUAL INFORMATION
Panin, G. (2013) · International Journal of Artificial Intelligence Tools · doi:10.1142/s0218213013600154 · Cited by 1
Brain PET Attenuation Correction without CT: An Investigation
Dewan, M., Zhan, Y., Hermosillo, G., Jian, B., & Zhou, X. S. (2013) · International Workshop on Pattern Recognition in NeuroImaging · doi:10.1109/prni.2013.37 · Cited by 1
Self-citationInformation theoretic measures and their applications to image registration and segmentation
Vemuri, B. C., & Wang, F. (2006) · Cited by 1
Guo, S., Lv, H., Liu, Y., Zhang, R., & Li, J. (2016) · Mathematical Problems in Engineering · doi:10.1155/2016/9491326 · Cited by 1
Lee, S. M., Kim, S. S., Hwang, H. J., & Seo, J. B. (2017) · Springer eBooks · doi:10.1007/978-3-662-47178-4_8 · Cited by 1
- Nonparametric: Demons, Diffusion, and Viscous-Fluid Approaches
Sarrut, D., & Vandemeulebroucke, J. (2016) · CRC Press eBooks · doi:10.1201/b15359-14 · Cited by 1
Kubo, H., Nemoto, A., Ukon, N., & Ito, H. (2021) · Radiological Physics and Technology · doi:10.1007/s12194-020-00605-z · Cited by 1
First Order Locally Orderless Registration
Darkner, S., Tascón-Vidarte, J. D., & Lauze, F. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-75549-2_15 · Cited by 1
A new similarity measure for deformable image registration based on intensity matching
Lu, Y., Sun, Y., Liao, R., & Ong, S. H. (2013) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2013.6556455 · Cited by 1
Non-rigid image registration using mutual information
Maes, F., D’Agostino, E., Loeckx, D., Wouters, J., Vandermeulen, D., & Suetens, P. (2007) · Physica-Verlag eBooks · doi:10.1007/978-3-7908-1709-6_8 · Cited by 1
Problem solving with well posedness analysis: Part 1
Liebrock, L. M. (2006) · Applied Mathematics and Computation · doi:10.1016/j.amc.2006.03.019 · Cited by 1
Tokuhisa, S., & Kaneko, K. (2009) · International Conference on Ubiquitous Information Management and Communication (IMCOM) · doi:10.1145/1516241.1516332 · Cited by 1
Semi-Rigid Registration of Remote Sensing Airborne Scanner Images
Cariou, C., & Chehdi, K. (2006) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2006.1660470 · 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
[Correlative imaging in cardiology. Principles and clinical application].
Kuwert, T., Römer, W., & Joachim Hornegger, A. (2007) · PubMed · doi:10.1007/s00059-007-2959-2 · Cited by 1
Elastic Registration for Biomedical Applications
Kybic, J., & Unser, M. A. (2007) · Springer eBooks · doi:10.1007/0-306-48608-3_9
Information-theoretic feature detection and its application to registration of ultrasound images
Wang, Z. W., Slabaugh, G., Ünal, G., & Fang, T. (2008) · Sabanci University
Quantitative and Qualitative Evaluation of Selected Lung MR Image Registration Techniques
Wujcicki, A., & Materka, A. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-11331-9_78
Kernel-Predictability: A New Information Measure and Its Application to Image Registration
Gómez-García, H. F., Marroquin, J. L., & Horebeek, J. V. (2006) · Lecture notes in computer science · doi:10.1007/11744078_39
Multimodal Three Dimensional Scene Reconstruction, The Gaussian Fields Framework
Boughorbel, F. (2005)
Hybrid Multimodal Deformable Registration with a Data-Driven Deformation Prior
Lu, Y., Sun, Y., Liao, R., & Ong, S. H. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-40843-4_6
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
Assembly method for multimodal image registration
Li, J., Chang, X., Xia, Y., & Han, Y. (2012) · IEEE International Conference on Granular Computing (GrC) · doi:10.1109/grc.2012.6468655
Edge preserving multi-modal registration based on gradient intensity self-similarity
Rott, T., Shriki, D., & Bendory, T. (2014) · IEEE Convention of Electrical and Electronics Engineers in Israel · doi:10.1109/eeei.2014.7005886
Closed-Form Relaxation for MRF-MAP Tissue Classification Using Discrete Laplace Equations
Roche, A. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-33418-4_44
Seyyedi, M. A. P., Miller, P., & Gribben, H. (2011) · British Machine Vision Conference (BMVC) · doi:10.5244/c.25.92
Image registration by minimization of Mapping Complexity
Myronenko, A., & Song, X. (2009) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition workshops · doi:10.1109/cvprw.2009.5204345 · Cited by 2
A variational approach for correspondence finding between three rectified images
Kaminski, J. Y., Belhdeb, M., & Teicher, M. (2007)
Osokin, A., Vetrov, D., Lebedev, A. V., Galatenko, V., Kropotov, D., & Anokhin, K. V. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-21946-7_7
PDE-Based Parallel Deformable Registration on a Dual Core Cluster
Chen, L., Jiang, M., Lin, Y., Zhou, J. W., & Chang, B. (2008) · International Conference on Intelligent Networks and Intelligent Systems · doi:10.1109/icinis.2008.131
IMAGE REGISTRATION USING COMPUTER TECHNIQUES: APPLICATIONS ON NUCLEAR MEDICINE IMAGES
Alves, R. D. S. (2013)
Diffusion Weighted Magnetic Resonance Image Analysis and Medical Image Registration
Zeng, Q. (2008) · University of Florida Digital Collections (University of Florida)
Recalage semi-rigide d'images de scanner aéroporté
Cariou, C., & Chehdi, K. (2005)
Applications of variational partial differential equation models in medical image processing
Huang, F., & Chen, Y. (2004)
Hahn, D. A. (2010) · OPUS FAU (Kooperativer Bibliotheksverbund Berlin-Brandenburg (KOBV), on behalf of the Universitätsbibliothek Erlangen-Nürnberg)
AN APPROACH TO NONRIGID US-MRI REGISTRATION OF PELVIC ORGANS FOR ENDOMETRIOSIS DIAGNOSIS
Vaida, M.-C. U. M.-F., Dragos, S.-S., & Voina, L. S. A. (2012)
LAVIR—Locally adaptive variational image registration
Barcelos, C. A. Z. (2017) · Computers & Mathematics with Applications · doi:10.1016/j.camwa.2016.12.012
Local Area Transform for Cross-Modality Correspondence Matching and Deep Scene RecognitionPreprint
Ryu, S. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1901.00927
Variational Image Registration for Inhomogeneous-Resolution Pairs
Hosoya, K., & Imiya, A. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-22368-7_22
Locally Orderless RegistrationPreprint
Darkner, S., & Jon Sporring, A. (2012) · arXiv (Cornell University) · doi:10.48550/arxiv.1205.5425
Matching and Registration of Structures in Computational Vision: Applications on Medical Images
Oliveira, F. P. M. (2012) · Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) · doi:10.34626/4qjz-6q57
Principles and Constraints of Nonrigid Registration
Giavri, Z., Costa, D. C., & Papanikolaou, N. K. (2020) · Medical radiology · doi:10.1007/978-3-030-38261-2_5
Hwang, H. J., Lee, S. M., & Seo, J. B. (2020) · Medical radiology · doi:10.1007/978-3-030-43539-4_8
First Order Locally Orderless RegistrationPreprint
Darkner, S., Tascón-Vidarte, J. D., & Lauze, F. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2108.04926
Li, J., Grist, J. T., Gleeson, F. V., & Papież, B. W. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-66958-3_16
Recalage variationnel non rigide statistique référencé région
Rougon, N. F., Discher, A., & Preteux, F. J. (2005) · HAL
A hybrid L-BFGS and Gauss–Newton approach for multimodal diffeomorphic image registration
Li, Y., Zhang, D., & Zhang, J. (2025) · Applied Mathematical Modelling · doi:10.1016/j.apm.2025.116506
Li, Y. (2018) · theses.fr (ABES) · doi:10.70675/6a3b3769zbc79z4869z96e3z720d9cae64e9 · Cited by 1
Multi-Modal Image Registration Problem Integrating Multi-Scale Strategy and Deep Learning
Zhang, J. (2026) · Mathematics · doi:10.3390/math14122131
Depth-Prior Guided Learning for Infrared-Visible Image Registration and Fusion
Zhang, Y., Yan, R., Wei, H., Ma, Y., Yu, B., & Zhong, W. (2026) · IEEE Signal Processing Letters · doi:10.1109/lsp.2026.3715133
3D image reconstruction from serial sections
Liu, Y. (2014) · Scholarly Commons (University of Pennsylvania)
Metadata
- Authors
- Hermosillo, G., Chefd'Hotel, C., & Faugeras, O.
- Affiliations
- Institut national de recherche en sciences et technologies du numérique (FR)
- ORCID
- Faugeras, Olivier
- Venue
- International Journal of Computer Vision
- Published
- 2002-12
- Volume
- 50
- Issue
- 3
- Pages
- 329-343
- ISSN
- 0920-5691 (ISSN-L)
- 1573-1405
- OpenAlex
- W1518961746
- Cited by
- 388
- References
- 71
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 4 · 2023: 5 · 2022: 4 · 2021: 12 · 2020: 8 · 2019: 12 · 2018: 7 · 2017: 12 · 2016: 8 · 2015: 16 · 2014: 28 · 2013: 27 · 2012: 30
- FWCI
- 19.13
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- International Journal of Computer Vision (publishedVersion)
- Funders
- National Science Foundation
- Institut national de recherche en informatique et en automatique (INRIA)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Image and Video Retrieval Techniques
- Keywords
- multimodal image registration, non-rigid registration, variational methods, statistical similarity measures, optical flow, well-posedness
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