A bi-ventricular cardiac atlas built from 1000+ high resolution MR images of healthy subjects and an analysis of shape and motion
Open accessAbstract
Atlases encode valuable anatomical and functional information from a population. In this work, a bi-ventricular cardiac atlas was built from a unique data set, which consists of high resolution cardiac MR images of 1000+ normal subjects. Based on the atlas, statistical methods were used to study the variation of cardiac shapes and the distribution of cardiac motion across the spatio-temporal domain. We have shown how statistical parametric mapping (SPM) can be combined with a general linear model to study the impact of gender and age on regional myocardial wall thickness. Finally, we have also investigated the influence of the population size on atlas construction and atlas-based analysis. The high resolution atlas, the statistical models and the SPM method will benefit more studies on cardiac anatomy and function analysis in the future.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482 · see citing works
Golub, G. (2012) · doi:10.56021/9781421407944 · Cited by 34,505 · see citing works
The Elements of Statistical Learning
Hastie, T., Friedman, J., & Tibshirani, R. (2001) · Springer Series in Statistics · doi:10.1007/978-0-387-21606-5 · Cited by 24,162 · see citing works
The control of the false discovery rate in multiple testing under dependency
Benjamini, Y., & Yekutieli, D. (2001) · The Annals of Statistics · doi:10.1214/aos/1013699998 · Cited by 10,490 · see citing works
Statistical parametric maps in functional imaging: A general linear approach
Friston, K. J., Holmes, A. P., Worsley, K. J., Poline, J. ‐., Frith, C. D., & Frackowiak, R. S. J. (1994) · Human Brain Mapping · doi:10.1002/hbm.460020402 · Cited by 9,688 · see citing works
Yushkevich, P. A., Piven, J., Hazlett, H. C., Smith, R. G., Ho, S., Gee, J. C., & Gerig, G. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.01.015 · Cited by 8,868 · see citing works
Voxel-Based Morphometry—The Methods
Ashburner, J., & Friston, K. J. (2000) · NeuroImage · doi:10.1006/nimg.2000.0582 · Cited by 8,676 · see citing works
A fast diffeomorphic image registration algorithm
Ashburner, J. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.07.007 · Cited by 8,122 · see citing works
Standardized Myocardial Segmentation and Nomenclature for Tomographic Imaging of the Heart
Cerqueira, M. D., Weissman, N. J., Dilsizian, V., Jacobs, A. K., Kaul, S., Laskey, W. K., Pennell, D. J., Rumberger, J. A., Ryan, T., & Verani, M. S. (2002) · Circulation · doi:10.1161/hc0402.102975 · Cited by 7,043 · see citing works
Nonrigid registration using free-form deformations: application to breast mr images
Rueckert, D., Sonoda, L. I., Hayes, C., Hill, D. L. G., Leach, M. O., & Hawkes, D. J. (1999) · IEEE Transactions on Medical Imaging · doi:10.1109/42.796284 · Cited by 5,265 · see citing works
Self-citationThresholding of statistical maps in functional neuroimaging using the false discovery rate
Genovese, C. R., Lazar, N. A., & Nichols, T. (2002) · NeuroImage · doi:10.1006/nimg.2001.1037 · Cited by 4,923 · see citing works
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 · see citing works
The Elements of Statistical Learning
Hastie, T. J., Tibshirani, R. J., & Friedman, J. H. (2009) · Springer series in statistics · doi:10.1007/b94608 · Cited by 4,111 · see citing works
Global atlas on cardiovascular disease prevention and control.
Mendis, S., Puska, P., & Norrving, B. G. (2011) · Virtual Defense Library (Ministerio de Defensa) · Cited by 2,691 · see citing works
Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration
Klein, A., Andersson, J., Ardekani, B. A., Ashburner, J., Avants, B., Chiang, M.-C., Christensen, G. E., Collins, D. L., Gee, J., Hellier, P., et al. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.12.037 · Cited by 2,227 · see citing works
Self-citationSchulz‐Menger, J., Bluemke, D. A., Bremerich, J., Flamm, S. D., Fogel, M. A., Friedrich, M. G., Kim, R. J., von Knobelsdorff‐Brenkenhoff, F., Kramer, C. M., Pennell, D. J., et al. (2013) · Journal of Cardiovascular Magnetic Resonance · doi:10.1186/1532-429x-15-35 · Cited by 2,113 · see citing works
Frackowiak, R. S. J. (1997) · Cited by 1,713 · see citing works
Statistical shape models for 3D medical image segmentation: A review
Heimann, T., & Meinzer, H.-P. (2009) · Medical Image Analysis · doi:10.1016/j.media.2009.05.004 · Cited by 1,424 · see citing works
Unbiased diffeomorphic atlas construction for computational anatomy
Joshi, S. C., Davis, B. C., Jomier, M., & Gerig, G. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.07.068 · Cited by 850 · see citing works
Geometric Means in a Novel Vector Space Structure on Symmetric Positive‐Definite Matrices
Arsigny, V., Fillard, P., Pennec, X., & Ayache, N. (2007) · SIAM Journal on Matrix Analysis and Applications · doi:10.1137/050637996 · Cited by 822 · see citing works
How Many Subjects Constitute a Study?
Friston, K. J., Holmes, A. P., & Worsley, K. J. (1999) · NeuroImage · doi:10.1006/nimg.1999.0439 · Cited by 814 · cited 1× · see citing works
“(Friston et al., 1999) and (Hayasaka et al., 2007) explored this question for brain image studies and suggested that random models and statistical power analysis can be used to determine the population size.”
Multi-Atlas Segmentation with Joint Label Fusion
Wang, H., Suh, J. W., Das, S. R., Pluta, J. B., Craige, C., & Yushkevich, P. A. (2013) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2012.143 · Cited by 796 · see citing works
Kitzman, D. W., SCHOLZ, D. G., Hagen, P. T., Ilstrup, D. M., & Edwards, W. D. (1988) · Mayo Clinic Proceedings · doi:10.1016/s0025-6196(12)64946-5 · Cited by 503 · see citing works
Average Brain Models: A Convergence Study
Guimond, A., Meunier, J., & Thirion, J. (2000) · Computer Vision and Image Understanding · doi:10.1006/cviu.1999.0815 · Cited by 431 · see citing works
Frangi, A. F., Rueckert, D., Schnabel, J. A., & Niessen, W. J. (2002) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2002.804426 · Cited by 382 · see citing works
Self-citationAutomatic Model-Based Segmentation of the Heart in CT Images
Ecabert, O., Peters, J., Schramm, H., Lorenz, C., von Berg, J., Walker, M. J. P., Vembar, M., Olszewski, M. E., Subramanyan, K., Lavi, G., et al. (2008) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2008.918330 · Cited by 368 · see citing works
Gender differences and normal left ventricular anatomy in an adult population free of hypertension
Salton, C. J., Chuang, M. L., O’Donnell, C. J., Kupka, M. J., Larson, M. G., Kissinger, K. V., Edelman, R. R., Levy, D. A., & Manning, W. J. (2002) · Journal of the American College of Cardiology · doi:10.1016/s0735-1097(02)01712-6 · Cited by 353 · see citing works
A dynamic 4D probabilistic atlas of the developing brain
Deprez, M., Aljabar, P., Srinivasan, L., Counsell, S. J., Doria, V., Serag, A., Gousias, I. S., Boardman, J. P., Rutherford, M., Edwards, A. D., et al. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.10.019 · Cited by 287 · see citing works
Self-citationFonseca, C. G., Backhaus, M., Bluemke, D. A., Britten, R. D., Chung, J. D., Cowan, B. R., Dinov, I. D., Finn, J. P., Hunter, P. J., Kadish, A. H., et al. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr360 · Cited by 281 · see citing works
Segmentation of 4D cardiac MR images using a probabilistic atlas and the EM algorithm
Lorenzo-Valdés, M. (2004) · Medical Image Analysis · doi:10.1016/j.media.2004.06.005 · Cited by 274 · see citing works
Cardiac Image Super-Resolution with Global Correspondence Using Multi-Atlas PatchMatch
Shi, W., Caballero, J., Ledig, C., Zhuang, X., Bai, W., Bhatia, K. K., de Marvao, A., Dawes, T. J. W., O’Regan, D. P., & Rueckert, D. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-40760-4_2 · Cited by 242 · see citing works
Self-citationHuman Atlas of the Cardiac Fiber Architecture: Study on a Healthy Population
Lombaert, H., Peyrat, J., Croisille, P., Rapacchi, S., Fanton, L., Farida Cheriet, A., Clarysse, P., Magnin, I. E., Delingette, H., & Ayache, N. (2012) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2012.2192743 · Cited by 227 · see citing works
A Registration-Based Propagation Framework for Automatic Whole Heart Segmentation of Cardiac MRI
Zhuang, X., Rhode, K., Razavi, R., Hawkes, D. J., & Sebastien Ourselin, A. (2010) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2010.2047112 · Cited by 223 · see citing works
Non-local statistical label fusion for multi-atlas segmentation
Asman, A. J., & Landman, B. A. (2012) · Medical Image Analysis · doi:10.1016/j.media.2012.10.002 · Cited by 217 · see citing works
Bai, W., Shi, W., O’Regan, D. P., Tong, T., Wang, H., Jamil‐Copley, S., Peters, N. S., & Rueckert, D. (2013) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2013.2256922 · Cited by 209 · see citing works
Self-citationSuinesiaputra, A., Cowan, B. R., Al‐Agamy, A. O., Elattar, M., Ayache, N., Fahmy, A. S., Khalifa, A. M., Medrano−Gracia, P., Jolly, M., Kadish, A. H., et al. (2013) · Medical Image Analysis · doi:10.1016/j.media.2013.09.001 · Cited by 206 · see citing works
Linear combination of transformations
Alexa, M. (2002) · ACM SIGGRAPH Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH) · doi:10.1145/566570.566592 · Cited by 189 · see citing works
Statistical shape model of atria, ventricles and epicardium from short- and long-axis MR images
Lötjönen, J. M. P. (2004) · Medical Image Analysis · doi:10.1016/j.media.2004.06.013 · Cited by 180 · see citing works
Automatic Construction of 3D Statistical Deformation Models Using Non-rigid Registration
Rueckert, D., Frangi, A. F., & Schnabel, J. (2001) · International Conference on Medical Image Computing and Computer-Assisted Intervention · doi:10.1007/3-540-45468-3_10 · Cited by 179 · see citing works
Self-citationComputational cardiac atlases: from patient to population and back
Young, A. A., & Frangi, A. F. (2008) · Experimental Physiology · doi:10.1113/expphysiol.2008.044081 · Cited by 138 · see citing works
Power and sample size calculation for neuroimaging studies by non-central random field theory
Hayasaka, S., Peiffer, A., Hugenschmidt, C., & Laurienti, P. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.06.009 · Cited by 133 · see citing works
Kiebel, S. J., & Mueller, K. (2015) · Elsevier eBooks · doi:10.1016/b978-0-12-397025-1.00317-1 · Cited by 119 · see citing works
Bayesian template estimation in computational anatomy
Ma, J., Miller, M. I., Trouvé, A., & Laurent Younes, B. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.03.056 · Cited by 105 · see citing works
An accurate, fast and robust method to generate patient-specific cubic Hermite meshes
Lamata, P., Niederer, S., Nordsletten, D., Barber, D. C., Roy, I., Hose, D. R., & Smith, N. P. (2011) · Medical Image Analysis · doi:10.1016/j.media.2011.06.010 · Cited by 104 · see citing works
Jacobi fields in groups of diffeomorphisms and applications
Laurent Younes, B. (2007) · Quarterly of Applied Mathematics · doi:10.1090/s0033-569x-07-01027-5 · Cited by 102 · see citing works
Spectral Log-Demons: Diffeomorphic Image Registration with Very Large Deformations
Lombaert, H., Grady, L. J., Pennec, X., Ayache, N., & Farida Cheriet, A. (2013) · International Journal of Computer Vision · doi:10.1007/s11263-013-0681-5 · Cited by 99 · see citing works
Medrano-Gracia, P., Cowan, B. R., Ambale-Venkatesh, B., Bluemke, D. A., Eng, J., Finn, J. P., Fonseca, C. G., Lima, J. A., Suinesiaputra, A., & Young, A. A. (2014) · Journal of Cardiovascular Magnetic Resonance · doi:10.1186/s12968-014-0056-2 · Cited by 98 · see citing works
Linear combination of transformations
Alexa, M. (2002) · ACM Transactions on Graphics · doi:10.1145/566654.566592 · Cited by 96 · see citing works
A High-Resolution Atlas and Statistical Model of the Human Heart From Multislice CT
Hoogendoorn, C., Duchateau, N., Sánchez‐Quintana, D., Whitmarsh, T., Sukno, F. M., Craene, M. D., Lekadir, K., & Frangi, A. F. (2012) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2012.2230015 · Cited by 91 · see citing works
Information Processing in Medical Imaging
Claridge, E., Preece, S., Taylor, C., & Noble, J. (2003) · Lecture notes in computer science · doi:10.1007/b11820 · Cited by 91 · see citing works
Suinesiaputra, A., Frangi, A. F., Kaandorp, T. A. M., Lamb, H. J., Bax, J. J., Reiber, J. H. C., & Lelieveldt, B. P. F. (2009) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2008.2008966 · Cited by 84 · see citing works
Encoding Probabilistic Brain Atlases Using Bayesian Inference
Leemput, K. V. (2008) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2008.2010434 · Cited by 78 · see citing works
2011 International Symposium on Biomedical Imaging
(2010) · IEEE Pulse · doi:10.1109/mpul.2010.938698 · Cited by 78 · see citing works
Bayesian Estimation of Regularization and Atlas Building in Diffeomorphic Image Registration
Zhang, M., Singh, N. P., & Fletcher, P. T. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-38868-2_4 · Cited by 76 · see citing works
Construction of a Statistical Model for Cardiac Motion Analysis Using Nonrigid Image Registration
Chandrashekara, R., Rao, A. W., Sanchez-Ortiz, G. I., Mohiaddin, R. H., & Rueckert, D. (2003) · Lecture notes in computer science · doi:10.1007/978-3-540-45087-0_50 · Cited by 73 · see citing works
Self-citationConstruction of a 4D Statistical Atlas of the Cardiac Anatomy and Its Use in Classification
Perperidis, D., Mohiaddin, R. H., & Rueckert, D. (2005) · Lecture notes in computer science · doi:10.1007/11566489_50 · Cited by 72 · see citing works
Self-citationMarchesseau, S., Delingette, H., Maxime Sermesant, B., Cabrera-Lozoya, R., Tobon‐Gomez, C., Moireau, P., Ventura, R. M. F. I., Lekadir, K., Hernandez, A. I., Garreau, M., et al. (2013) · Medical Image Analysis · doi:10.1016/j.media.2013.04.012 · Cited by 72 · see citing works
Duchateau, N., Craene, M. D., Piella, G., Silva, E., Doltra, A., Sitges, M., Bijnens, B. H., & Frangi, A. F. (2011) · Medical Image Analysis · doi:10.1016/j.media.2010.12.006 · Cited by 71 · see citing works
Nikitin, N. P., Loh, P. H., de Silva, R., Witte, K. K., Lukaschuk, E. I., Parker, A., Farnsworth, T. A., Alamgir, F. M., Clark, A. L., & Cleland, J. G. F. (2005) · International Journal of Cardiology · doi:10.1016/j.ijcard.2005.04.009 · Cited by 69 · see citing works
Temporal sparse free-form deformations
Shi, W., Jantsch, M., Aljabar, P., Pizarro, L., Bai, W., Wang, H., O’Regan, D. P., Zhuang, X., & Rueckert, D. (2013) · Medical Image Analysis · doi:10.1016/j.media.2013.04.010 · Cited by 62 · see citing works
Self-citationSpatial Transformation of Motion and Deformation Fields Using Nonrigid Registration
Rao, A. W., Chandrashekara, R., Sanchez-Ortiz, G. I., Mohiaddin, R. H., Aljabar, P., Hajnal, J. V., Puri, B. K., & Rueckert, D. (2004) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2004.828681 · Cited by 59 · see citing works
Self-citationEfficient Parallel Transport of Deformations in Time Series of Images: From Schild’s to Pole Ladder
Lorenzi, M., & Pennec, X. (2013) · Journal of Mathematical Imaging and Vision · doi:10.1007/s10851-013-0470-3 · Cited by 58 · see citing works
Kiebel, S. J. (2011) · Max Planck Digital Library · Cited by 58 · see citing works
Time sequence diffeomorphic metric mapping and parallel transport track time-dependent shape changes
Qiu, A., Albert, M., Laurent Younes, B., & Miller, M. I. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.10.039 · Cited by 51 · see citing works
de Marvao, A., Dawes, T. J. W., Shi, W., Minas, C., Keenan, N., Diamond, T., Durighel, G., Montana, G., Rueckert, D., Cook, S. A., et al. (2014) · Journal of Cardiovascular Magnetic Resonance · doi:10.1186/1532-429x-16-16 · Cited by 48 · see citing works
Self-citationTransport of Relational Structures in Groups of Diffeomorphisms
Laurent Younes, B., Qiu, A., Winslow, R. L., & Miller, M. I. (2008) · Journal of Mathematical Imaging and Vision · doi:10.1007/s10851-008-0074-5 · Cited by 47 · see citing works
Big Heart Data: Advancing Health Informatics Through Data Sharing in Cardiovascular Imaging
Suinesiaputra, A., Medrano-Gracia, P., Cowan, B. R., & Young, A. A. (2015) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2014.2370952 · Cited by 45 · see citing works
McLeod, K., Maxime Sermesant, B., Beerbaum, P., & Pennec, X. (2015) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2015.2405579 · Cited by 39 · see citing works
Bilinear Models for Spatio-Temporal Point Distribution Analysis
Hoogendoorn, C., Sukno, F. M., Ordás, S., & Frangi, A. F. (2009) · International Journal of Computer Vision · doi:10.1007/s11263-009-0212-6 · Cited by 37 · see citing works
Building and using a statistical 3D motion atlas for analyzing myocardial contraction in MRI
Rougon, N., Petitjean, C., & Prêteux, F. (2004) · SPIE Medical Imaging · doi:10.1117/12.535609 · Cited by 28 · see citing works
Computational Anatomy Atlas of the Heart
Ordás, S., Oubel, E., Sebastián, R., & Frangi, A. F. (2007) · International symposium on image and signal processing and analysis/ISPA ... · doi:10.1109/ispa.2007.4383715 · Cited by 27 · see citing works
SPM to the heart: Mapping of 4D continuous velocities for motion abnormality quantification
Craene, M. D., Duchateau, N., Tobon‐Gomez, C., Ghafaryasl, B., Piella, G., Rhode, K., & Frange, A. F. (2012) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2012.6235582 · Cited by 16 · see citing works
An Atlas for Cardiac MRI Regional Wall Motion and Infarct Scoring
Medrano−Gracia, P., Suinesiaputra, A., Cowan, B. R., Bluemke, D. A., Frangi, A. F., Lee, D. C., Lima, J. A. C., & Young, A. A. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-36961-2_22 · Cited by 12 · see citing works
A framework for the merging of pre-existing and correspondenceless 3D statistical shape models
Pereañez, M., Lekadir, K., Butakoff, C., Hoogendoorn, C., & Frangi, A. F. (2014) · Medical Image Analysis · doi:10.1016/j.media.2014.05.009 · Cited by 12 · see citing works
Which Reorientation Framework for the Atlas-Based Comparison of Motion from Cardiac Image Sequences?
Duchateau, N., Craene, M. D., Pennec, X., Merino, B., Sitges, M., & Bijnens, B. H. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-33555-6_3 · Cited by 11 · see citing works
Flagged first, then by citations
4 of the 79 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Oktay, O., Ferrante, E., Kamnitsas, K., Heinrich, M., Bai, W., Caballero, J., Cook, S. A., de Marvao, A., Dawes, T., O'Regan, D. P., et al. (2018) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2017.2743464 · Cited by 751 · see citing works
“Each image pair is acquired from a healthy subject using a standard imaging protocol [4], [15].”
MethodSelf-citationTitin-truncating variants affect heart function in disease cohorts and the general population
Schäfer, S., de Marvao, A., Adami, E., Fiedler, L. R., Ng, B., Khin, E. S. W., Rackham, O. J. L., van Heesch, S., Pua, C. J., Kui, M., et al. (2016) · Nature Genetics · doi:10.1038/ng.3719 · Cited by 363 · see citing works
Self-citationDeep Learning Approaches for Data Augmentation in Medical Imaging: A Review
Kebaili, A., Lapuyade‐Lahorgue, J., & Ruan, S. (2023) · Journal of Imaging · doi:10.3390/jimaging9040081 · Cited by 308 · see citing works
Learning a Probabilistic Model for Diffeomorphic Registration
Krebs, J., Delingette, H., Mailhé, B., Ayache, N., & Mansi, T. (2019) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2019.2897112 · Cited by 230 · see citing works
Dawes, T. J. W., de Marvao, A., Shi, W., Fletcher, T., Watson, G. M. J., Wharton, J., Rhodes, C. J., Howard, L., Gibbs, J. S. R., Rueckert, D., et al. (2017) · Radiology · doi:10.1148/radiol.2016161315 · Cited by 234 · see citing works
Self-citationDeep-learning cardiac motion analysis for human survival prediction
Bello, G. A., Dawes, T. J. W., Duan, J., Biffi, C., de Marvao, A., Howard, L. S. G. E., Gibbs, J. S. R., Wilkins, M. R., Cook, S. A., Rueckert, D., et al. (2019) · Nature Machine Intelligence · doi:10.1038/s42256-019-0019-2 · Cited by 231 · see citing works
Self-citationGenetic and functional insights into the fractal structure of the heart
Meyer, H. V., Dawes, T. J. W., Serrani, M., Bai, W., Tokarczuk, P. F., Cai, J., de Marvao, A., Henry, A., Lumbers, R. T., Gierten, J., et al. (2020) · Nature · doi:10.1038/s41586-020-2635-8 · Cited by 137 · see citing works
Self-citationToward a Common Coordinate Framework for the Human Body
Rood, J., Stuart, T., Ghazanfar, S., Biancalani, T., Fisher, E., Butler, A., Hupalowska, A., Gaffney, L., Mauck, W. M., Eraslan, G., et al. (2019) · Cell · doi:10.1016/j.cell.2019.11.019 · Cited by 115 · see citing works
Statistical Shape Modeling of the Left Ventricle: Myocardial Infarct Classification Challenge
Suinesiaputra, A., Dhooge, J., Duchateau, N., Ehrhardt, J., Frangi, A. F., Gooya, A., Grau, V., Lekadir, K., Lu, A., Mukhopadhyay, A., et al. (2018) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2017.2652449 · Cited by 95 · see citing works
Self-citationMauger, C., Gilbert, K., Lee, A. M., Sanghvi, M. M., Aung, N., Fung, K., Carapella, V., Piechnik, S. K., Neubauer, S., Petersen, S. E., et al. (2019) · Journal of Cardiovascular Magnetic Resonance · doi:10.1186/s12968-019-0551-6 · Cited by 78 · see citing works
Biffi, C., Oktay, O., Tarroni, G., Bai, W., de Marvao, A., Doumou, G., Rajchl, M., Bedair, R., Prasad, S. K., Cook, S. A., et al. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-00934-2_52 · Cited by 80 · see citing works
Self-citationStratified Decision Forests for Accurate Anatomical Landmark Localization in Cardiac Images
Oktay, O., Bai, W., Guerrero, R., Rajchl, M., de Marvao, A., O’Regan, D. P., Cook, S. A., Heinrich, M. P., Glocker, B., & Rueckert, D. (2016) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2016.2597270 · Cited by 74 · see citing works
Self-citationBanerjee, A., Camps, J., Zacur, E., Andrews, C. M., Rudy, Y., Choudhury, R. P., Rodríguez, B., & Grau, V. (2021) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2020.0257 · Cited by 73 · see citing works
Javeed, A., Khan, S. U., Ali, L., Ali, S. M., Imrana, Y., & Rahman, A. (2022) · Computational and Mathematical Methods in Medicine · doi:10.1155/2022/9288452 · Cited by 72 · see citing works
RetractedXia, Y., Ravikumar, N., Greenwood, J. P., Neubauer, S., Petersen, S. E., & Frangi, A. F. (2021) · Medical Image Analysis · doi:10.1016/j.media.2021.102037 · Cited by 69 · see citing works
Nagel, C., Schuler, S., Dössel, O., & Loewe, A. (2021) · Medical Image Analysis · doi:10.1016/j.media.2021.102210 · Cited by 66 · see citing works
Fedele, M., & Quarteroni, A. M. (2021) · International Journal for Numerical Methods in Biomedical Engineering · doi:10.1002/cnm.3435 · Cited by 65 · see citing works
Radiomics Signatures of Cardiovascular Risk Factors in Cardiac MRI: Results From the UK Biobank
Cetin, I., Raisi‐Estabragh, Z., Petersen, S. E., Napel, S. A., Piechnik, S. K., Neubauer, S., Ballester, M. Á. G., Cámara, Ó., & Lekadir, K. (2020) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2020.591368 · Cited by 61 · see citing works
Myocardial Radiomics in Cardiac MRI
Hassani, C., Saremi, F., Varghese, B. A., & Duddalwar, V. A. (2019) · American Journal of Roentgenology · doi:10.2214/ajr.19.21986 · Cited by 57 · see citing works
A Radiomics Approach to Computer-Aided Diagnosis with Cardiac Cine-MRI
Cetin, I., Sanroma, G., Petersen, S. E., Napel, S. A., Cámara, Ó., Ballester, M.-A. G., & Lekadir, K. (2018) · Lecture notes in computer science · doi:10.1007/978-3-319-75541-0_9 · Cited by 55 · see citing works
Duchateau, N., Maxime Sermesant, B., Delingette, H., & Ayache, N. (2017) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2017.2714343 · Cited by 53 · see citing works
Decourt, C., & Duong, L. (2020) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2020.103884 · Cited by 53 · see citing works
Campos, J. D. O., Sundnes, J., dos Santos, R. W., & Rocha, B. M. (2020) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2019.0381 · Cited by 50 · see citing works
Comparison of novel ventricular pacing strategies using an electro-mechanical simulation platform
Meiburg, R., Rijks, J. H. J., Beela, A. S., Bressi, E., Grieco, D., Delhaas, T., LUERMANS, J. G. L. M., Prinzen, F. W., Vernooy, K., & Lumens, J. (2023) · EP Europace · doi:10.1093/europace/euad144 · Cited by 46 · see citing works
Automated Detection of Motion Artefacts in MR Imaging Using Decision Forests
Lorch, B., Vaillant, G., Baumgartner, C. F., Bai, W., Rueckert, D., & Maier, A. (2017) · Journal of Medical Engineering · doi:10.1155/2017/4501647 · Cited by 46 · see citing works
Self-citationGilbert, K., Bai, W., Mauger, C., Medrano−Gracia, P., Suinesiaputra, A., Lee, A. M., Sanghvi, M. M., Aung, N., Piechnik, S. K., Neubauer, S., et al. (2019) · Scientific Reports · doi:10.1038/s41598-018-37916-6 · Cited by 46 · see citing works
Self-citationSinclair, M. D., Schuh, A., Hahn, K., Petersen, K., Bai, Y., Batten, J., Schaap, M., & Glocker, B. (2022) · Medical Image Analysis · doi:10.1016/j.media.2022.102383 · Cited by 45 · see citing works
Beetz, M., Banerjee, A., & Grau, V. (2022) · Frontiers in Physiology · doi:10.3389/fphys.2022.886723 · Cited by 41 · see citing works
Peressutti, D., Sinclair, M. D., Bai, W., Jackson, T., Ruijsink, B., Nordsletten, D., Asner, L., Hadjicharalambous, M., Rinaldi, C. A., Rueckert, D., et al. (2016) · Medical Image Analysis · doi:10.1016/j.media.2016.10.002 · Cited by 40 · see citing works
Self-citationAnton, E. P., Ruijsink, B., Gerber, B. L., Amzulescu, M. S., Langet, H., Craene, M. D., Schnabel, J. A., Piro, P., & King, A. P. (2018) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2018.2865669 · Cited by 40 · see citing works
Schuler, S., Pilia, N., Potyagaylo, D., & Loewe, A. (2021) · Medical Image Analysis · doi:10.1016/j.media.2021.102247 · Cited by 40 · see citing works
Surface Mesh Reconstruction from Cardiac MRI Contours
Villard, B., Grau, V., & Zacur, E. (2018) · Journal of Imaging · doi:10.3390/jimaging4010016 · Cited by 39 · see citing works
Artificial Intelligence in Cardiac Imaging With Statistical Atlases of Cardiac Anatomy
Gilbert, K., Mauger, C., Young, A. A., & Suinesiaputra, A. (2020) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2020.00102 · Cited by 38 · see citing works
Three-dimensional cardiovascular imaging-genetics: a mass univariate framework
Biffi, C., de Marvao, A., Attard, M., Dawes, T. J. W., Whiffin, N., Bai, W., Shi, W., Francis, C., Meyer, H. V., Buchan, R. J., et al. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx552 · Cited by 37 · see citing works
Self-citationBeetz, M., Banerjee, A., Ossenberg-Engels, J., & Grau, V. (2023) · Medical Image Analysis · doi:10.1016/j.media.2023.102975 · Cited by 36 · see citing works
Rodríguez‐Cantano, R., Sundnes, J., & Rognes, M. E. (2019) · International Journal for Numerical Methods in Biomedical Engineering · doi:10.1002/cnm.3178 · Cited by 35 · see citing works
Fractal Analysis of Right Ventricular Trabeculae in Pulmonary Hypertension
Dawes, T. J. W., Cai, J., Quinlan, M., de Marvao, A., Ostrowski, P. J., Tokarczuk, P. F., Watson, G. M. J., Wharton, J., Howard, L., Gibbs, J. S. R., et al. (2018) · Radiology · doi:10.1148/radiol.2018172821 · Cited by 35 · see citing works
Self-citationConstructing and optimizing 3D atlases from 2D data with application to the developing mouse brain
Young, D. M., Darbandi, S. F., Schwartz, G., Bonzell, Z., Yuruk, D., Nojima, M., Golé, L., Rubenstein, J. L. R., Yu, W., & Sanders, S. (2021) · eLife · doi:10.7554/elife.61408 · Cited by 35 · see citing works
Corden, B., de Marvao, A., Dawes, T. J. W., Shi, W., Rueckert, D., Cook, S. A., & O’Regan, D. P. (2016) · Journal of Cardiovascular Magnetic Resonance · doi:10.1186/s12968-016-0251-4 · Cited by 34 · see citing works
Self-citationDeepMesh: Mesh-Based Cardiac Motion Tracking Using Deep Learning
Meng, Q., Bai, W., O’Regan, D. P., & Rueckert, D. (2023) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2023.3340118 · Cited by 33 · see citing works
Self-citationA multimodal spatiotemporal cardiac motion atlas from MR and ultrasound data
Anton, E. P., Sinclair, M. D., Gerber, B. L., Amzulescu, M. S., Langet, H., Craene, M. D., Aljabar, P., Piro, P., & King, A. P. (2017) · Medical Image Analysis · doi:10.1016/j.media.2017.06.002 · Cited by 33 · see citing works
Interpretable cardiac anatomy modeling using variational mesh autoencoders
Beetz, M., Acero, J. C., Banerjee, A., Eitel, I., Zacur, E., Lange, T., Stiermaier, T., Evertz, R., Backhaus, S. J., Thiele, H., et al. (2022) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2022.983868 · Cited by 32 · see citing works
A deep learning approach for fully automated cardiac shape modeling in tetralogy of Fallot
Govil, S., Crabb, B. T., Deng, Y., Toso, L. D., Anton, E. P., Pushparajah, K., Hegde, S. R., Perry, J. C., Omens, J. H., Hsiao, A., et al. (2023) · Journal of Cardiovascular Magnetic Resonance · doi:10.1186/s12968-023-00924-1 · Cited by 31 · see citing works
Sarmah, M., Neelima, A., & Singh, H. R. (2023) · Visual Computing for Industry Biomedicine and Art · doi:10.1186/s42492-023-00142-7 · Cited by 32 · see citing works
Variational autoencoders for 3D data processing
Molnár, S., & Tamás, L. (2024) · Artificial Intelligence Review · doi:10.1007/s10462-023-10687-x · Cited by 31 · see citing works
Goubergrits, L., Vellguth, K., Obermeier, L., Schlief, A., Tautz, L., Brüning, J., Lamecker, H., Szengel, A., Nemchyna, O., Knosalla, C., et al. (2022) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2022.901902 · Cited by 31 · see citing works
Machine Learning Approaches for Myocardial Motion and Deformation Analysis
Duchateau, N., King, A. P., & Craene, M. D. (2020) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2019.00190 · Cited by 31 · see citing works
Computer Modeling of the Heart for ECG Interpretation—A Review
Dössel, O., Luongo, G., Nagel, C., & Loewe, A. (2021) · Hearts · doi:10.3390/hearts2030028 · Cited by 29 · see citing works
Artificial Intelligence for Cardiac Imaging-Genetics Research
de Marvao, A., Dawes, T. J. W., & O’Regan, D. P. (2020) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2019.00195 · Cited by 30 · see citing works
Self-citationBiventricular Surface Reconstruction From Cine Mri Contours Using Point Completion Networks
Beetz, M., Banerjee, A., & Grau, V. (2021) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi48211.2021.9434040 · Cited by 28 · see citing works
Joyce, T., Buoso, S., Stoeck, C. T., & Kozerke, S. (2022) · Medical Image Analysis · doi:10.1016/j.media.2022.102445 · Cited by 27 · see citing works
Biffi, C., Cerrolaza, J. J., Tarroni, G., de Marvao, A., Cook, S. A., O’Regan, D. P., & Rueckert, D. (2019) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2019.8759328 · Cited by 27 · see citing works
Self-citationSinclair, M. D., Bai, W., Anton, E. P., Oktay, O., Rueckert, D., & King, A. P. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_38 · Cited by 26 · see citing works
Self-citationSex-Dependent QRS Guidelines for Cardiac Resynchronization Therapy Using Computer Model Predictions
Lee, A., O’Regan, D. P., Gould, J., Sidhu, B. S., Sieniewicz, B., Plank, G., Warriner, D., Lamata, P., Rinaldi, C. A., & Niederer, S. (2019) · Biophysical Journal · doi:10.1016/j.bpj.2019.08.025 · Cited by 24 · see citing works
Self-citationBeetz, M., Banerjee, A., & Grau, V. (2022) · Lecture notes in computer science · doi:10.1007/978-3-030-93722-5_9 · Cited by 24 · see citing works
Attard, M., Dawes, T. J. W., de Marvao, A., Biffi, C., Shi, W., Wharton, J., Rhodes, C. J., Ghataorhe, P., Gibbs, J. S. R., Howard, L., et al. (2018) · European Heart Journal - Cardiovascular Imaging · doi:10.1093/ehjci/jey175 · Cited by 24 · see citing works
Self-citationEffects of left ventricle wall thickness uncertainties on cardiac mechanics
Campos, J. D. O., Sundnes, J., dos Santos, R. W., & Rocha, B. M. (2019) · Biomechanics and Modeling in Mechanobiology · doi:10.1007/s10237-019-01153-1 · Cited by 24 · see citing works
Soltanmohammadi, P., Elwell, J. A., Veeraraghavan, V. P., Athwal, G. S., & Willing, R. T. (2020) · Journal of Biomechanical Engineering · doi:10.1115/1.4047664 · Cited by 23 · see citing works
Atlas Based Computational Analysis of Heart Shape and Function in Congenital Heart Disease
Gilbert, K., Forsch, N., Hegde, S., Mauger, C., Omens, J., Perry, J., Pontré, B., Suinesiaputra, A., Young, A., & McCulloch, A. (2018) · Journal of Cardiovascular Translational Research · doi:10.1007/s12265-017-9778-5 · Cited by 22 · see citing works
Xanthis, C. G., Filos, D., Haris, K., & Aletras, A. H. (2020) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2020.105817 · Cited by 22 · see citing works
A personalized time-resolved 3D mesh generative model for unveiling normal heart dynamics
Qiao, M., McGurk, K. A., Wang, S., Matthews, P. M., O’Regan, D. P., & Bai, W. (2025) · Nature Machine Intelligence · doi:10.1038/s42256-025-01035-5 · Cited by 21 · see citing works
Self-citationCarminati, C., Piazzese, C., Pepi, M., Tamborini, G., Gripari, P., Pontone, G., Krause, R., Auricchio, A., Lang, R. M., & Caiani, E. G. (2018) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2018.03.013 · Cited by 19 · see citing works
Cardiac left ventricular volumes prediction method based on atlas location and deep learning
Luo, G., Dong, S., Wang, K., & Zhang, H. (2016) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm.2016.7822759 · Cited by 18 · see citing works
Ventricle Surface Reconstruction from Cardiac MR Slices Using Deep Learning
Xu, H., Zacur, E., Schneider, J. E., & Grau, V. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-21949-9_37 · Cited by 17 · see citing works
Statistical Shape Models of the Heart: Applications to Cardiac Imaging
Piazzese, C., Carminati, C., Pepi, M., & Caiani, E. G. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-810493-4.00019-5 · Cited by 16 · see citing works
Pilia, N., Schuler, S., Rees, M., Moik, G., Potyagaylo, D., Dössel, O., & Loewe, A. (2023) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2023.102619 · Cited by 16 · see citing works
Sander, J., de Vos, B. D., Bruns, S., Planken, R. N., Viergever, M. A., Leiner, T., & Išgum, I. (2023) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2023.107266 · Cited by 16 · see citing works
Chen, Z., Ren, H., Li, Q., & Li, X. (2024) · Computerized Medical Imaging and Graphics · doi:10.1016/j.compmedimag.2024.102389 · Cited by 15 · see citing works
Prins, B. P., Leitsalu, L., Pärna, K., Fischer, K., Metspalu, A., Haller, T., & Snieder, H. (2021) · Journal of Personalized Medicine · doi:10.3390/jpm11050358 · Cited by 15 · see citing works
A probabilistic deep motion model for unsupervised cardiac shape anomaly assessment
Zakeri, A., Hokmabadi, A., Ravikumar, N., Frangi, A. F., & Gooya, A. (2021) · Medical Image Analysis · doi:10.1016/j.media.2021.102276 · Cited by 15 · see citing works
Deep learning in 3D cardiac reconstruction: a systematic review of methodologies and dataset
Pandey, R. K., & Rathore, Y. K. (2025) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-024-03273-y · Cited by 14 · see citing works
Bhuva, A., Treibel, T. A., de Marvao, A., Biffi, C., Dawes, T. J. W., Doumou, G., Bai, W., Patel, K. P., Boubertakh, R., Rueckert, D., et al. (2019) · European Heart Journal - Cardiovascular Imaging · doi:10.1093/ehjci/jez166 · Cited by 14 · see citing works
Self-citationPoint2Mesh-Net: Combining Point Cloud and Mesh-Based Deep Learning for Cardiac Shape Reconstruction
Beetz, M., Banerjee, A., & Grau, V. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-23443-9_26 · Cited by 13 · see citing works
Buoso, S., Joyce, T., Schulthess, N., & Kozerke, S. (2023) · Journal of Cardiovascular Magnetic Resonance · doi:10.1186/s12968-023-00934-z · Cited by 12 · see citing works
4D Myocardium Reconstruction with Decoupled Motion and Shape Model
Yuan, X., Liu, C., & Wang, Y. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.01943 · Cited by 12 · see citing works
Asaeikheybari, G., El‐Harasis, M. A., Gupta, A. B., Shoemaker, M. B., Barnard, J., Hunter, J. G., PASSMAN, R. S., Sun, H., Kim, H. S., Schilling, T., et al. (2024) · Circulation Arrhythmia and Electrophysiology · doi:10.1161/circep.123.012679 · Cited by 12 · see citing works
Piazzese, C., Carminati, C., Colombo, A., Krause, R., Potse, M., Auricchio, A., Weinert, L., Tamborini, G., Pepi, M., Lang, R. M., et al. (2016) · Journal of Electrocardiology · doi:10.1016/j.jelectrocard.2016.03.017 · Cited by 12 · see citing works
Asheghan, M. M., Javadikasgari, H., Attary, T., Rouhollahi, A., Straughan, R., Willi, J. N., Awal, R., Sabe, A. A., de la Cruz, K. I., & Nezami, F. R. (2023) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2023.1130152 · Cited by 10 · see citing works
Optimised Misalignment Correction from Cine MR Slices Using Statistical Shape Model
Banerjee, A., Zacur, E., Choudhury, R. P., & Grau, V. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-80432-9_16 · Cited by 10 · see citing works
Ma, C., Luo, G., & Wang, K. (2017) · BioMed Research International · doi:10.1155/2017/8381094 · Cited by 9 · see citing works
Galazis, C., Shepperd, S., Brouwer, E. J. P., Queirós, S., Alskaf, E., Anjari, M., Chiribiri, A., Lee, J., Bharath, A. A., & Varela, M. (2025) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2025.3526364 · Cited by 8 · see citing works
Kidney shape statistical analysis: associations with disease and anthropometric factors
Thanaj, M., Basty, N., Cule, M., Sorokin, E. P., Whitcher, B. J., Srinivasan, R., Lennon, R., Bell, J. D., & Thomas, E. L. (2023) · BMC Nephrology · doi:10.1186/s12882-023-03407-8 · Cited by 8 · see citing works
Sinclair, M., Peressutti, D., Anton, E. P., Bai, W., Rivolo, S., Webb, J., Claridge, S., Jackson, T., Nordsletten, D., Hadjicharalambous, M., et al. (2017) · Medical Image Analysis · doi:10.1016/j.media.2017.10.004 · Cited by 8 · see citing works
Self-citationMountris, K. A., Bourantas, G. C., Millán, R. D., Joldes, G. R., Miller, K., Pueyo, E., & Wittek, A. (2019) · Conicet · Cited by 8 · see citing works
Moscoloni, B., Beeche, C., Chirinos, J. A., Segers, P., & Peirlinck, M. (2025) · The Journal of Physiology · doi:10.1113/jp288667 · Cited by 7 · see citing works
Explainable Anatomical Shape Analysis Through Deep Hierarchical Generative Models
Biffi, C., Cerrolaza, J. J., Tarroni, G., Bai, W., de Marvao, A., Oktay, O., Ledig, C., Folgoc, L. L., Kamnitsas, K., Doumou, G., et al. (2020) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2020.2964499 · Cited by 7 · see citing works
Self-citationMountris, K. A., Bourantas, G. C., Millán, D., Joldes, G. R., Miller, K., Pueyo, E., & Wittek, A. (2019) · International Journal for Numerical Methods in Engineering · doi:10.1002/nme.6218 · Cited by 7 · see citing works
Gopalan, D., & Gibbs, J. S. R. (2020) · Diagnostics · doi:10.3390/diagnostics10121004 · Cited by 7 · see citing works
Beetz, M., Banerjee, A., Li, L., Camps, J., Rodríguez, B., & Grau, V. (2025) · Computerized Medical Imaging and Graphics · doi:10.1016/j.compmedimag.2025.102587 · Cited by 6 · see citing works
Functional Characterization of a Spectrum of Novel Romano-Ward Syndrome KCNQ1 Variants
Rinné, S., Oertli, A., Nagel, C., Tomsits, P., Jenewein, T., Kääb, S., Kauferstein, S., Loewe, A., Beckmann, B. M., & Decher, N. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms24021350 · Cited by 6 · see citing works
Liver shape analysis using statistical parametric maps at population scale
Thanaj, M., Basty, N., Cule, M., Sorokin, E. P., Whitcher, B. J., Bell, J. D., & Thomas, E. L. (2024) · BMC Medical Imaging · doi:10.1186/s12880-023-01149-5 · Cited by 6 · see citing works
Parallel Transport of Surface Deformations from Pole Ladder to Symmetrical Extension
Jia, S., Duchateau, N., Moceri, P., Maxime Sermesant, B., & Pennec, X. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-04747-4_11 · Cited by 6 · see citing works
Correcting bias in cardiac geometries derived from multimodal images using spatiotemporal mapping
Zhao, D., Mauger, C., Gilbert, K., Wang, V. Y., Quill, G., Sutton, T., Lowe, B., Legget, M., Ruygrok, P., Doughty, R., et al. (2023) · Scientific Reports · doi:10.1038/s41598-023-33968-5 · Cited by 3 · see citing works
Second order kinematic surface fitting in anatomical structures
Wimmer, W., & Delingette, H. (2025) · Medical Image Analysis · doi:10.1016/j.media.2025.103488 · Cited by 6 · see citing works
McLeod, K., Tøndel, K., Calvet, L., Maxime Sermesant, B., & Pennec, X. (2018) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2018.2816519 · Cited by 6 · see citing works
Thanaj, M., Basty, N., Cule, M., Sorokin, E. P., Whitcher, B. J., Srinivasan, R., Bell, J. D., & Thomas, E. L. (2025) · International Journal of Obesity · doi:10.1038/s41366-025-01829-y · Cited by 5 · see citing works
Wang, Y., McKeown, T., Hao, Y. W., An, H., Gach, H. M., Robinson, C. G., Cuculich, P. S., & Yang, D. (2025) · Medical Physics · doi:10.1002/mp.18115 · Cited by 5 · see citing works
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 · see citing works
Schweitzer, R., de Marvao, A., Shah, M., Inglese, P., Kellman, P., Berry, A., Statton, B. K., & O’Regan, D. P. (2025) · Radiology Cardiothoracic Imaging · doi:10.1148/ryct.240175 · Cited by 5 · see citing works
Self-citationMass Univariate Regression Analysis for Three-Dimensional Liver Image-Derived Phenotypes
Thanaj, M., Basty, N., Liu, Y., Cule, M., Sorokin, E. P., Thomas, E. L., Bell, J. D., & Whitcher, B. J. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-80432-9_13 · Cited by 5 · see citing works
- Authors
- Bai, W., Shi, W., de Marvao, A., Dawes, T. J. W., O’Regan, D. P., Cook, S. A., & Rueckert, D.
- Affiliations
- Imperial College London (GB)
- Hammersmith Hospital (GB)
- National University of Singapore (SG)
- Corresponding author
- Bai, Wenjia
- Venue
- Medical Image Analysis
- Publisher
- Elsevier BV
- Published
- 2015-12
- Volume
- 26
- Issue
- 1
- Pages
- 133-145
- ISSN
- 1361-8415 (ISSN-L)
- OpenAlex
- W1872336954
- Cited by
- 171
- References
- 79
- Citations by year
- 2026: 18 · 2025: 21 · 2024: 12 · 2023: 20 · 2022: 15 · 2021: 13 · 2020: 16 · 2019: 20 · 2018: 16 · 2017: 13 · 2016: 7
- FWCI
- 10.42
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- cc-by-nc-nd
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- Locations
- Medical Image Analysis (publishedVersion)
- PubMed (publishedVersion)
- National University of Singapore (submittedVersion)
- Spiral (Imperial College London) (submittedVersion, cc-by-nc-nd)
- Funders
- Engineering and Physical Sciences Research Council (EPSRC), UK (EP/K030523/1)
- Medical Research Council (MRC), UK
- National Institute for Health Research
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Cardiac Imaging and Diagnostics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Keywords
- cardiac motion, statistical parametric mapping, myocardial wall thickness, age and gender effects, population size, atlas construction, healthy volunteers
- MeSH terms
- Computer Simulation, Heart Ventricles, Humans, Image Interpretation, Computer-Assisted, Models, Anatomic, Models, Cardiovascular, Pattern Recognition, Automated, Radiology Information Systems, Reference Values, Sensitivity and Specificity, Subtraction Technique, Reproducibility of Results, Models, Statistical, Databases, Factual, Magnetic Resonance Imaging, Cine
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
