{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T02:10:31Z","timestamp":1781489431826,"version":"3.54.1"},"reference-count":75,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,2,23]],"date-time":"2026-02-23T00:00:00Z","timestamp":1771804800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100007065","name":"NVIDIA Corporation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100007065","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100013342","name":"National Institute for Health Research Imperial Biomedical Research Centre","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100013342","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004543","name":"China Scholarship Council","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004543","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000288","name":"The Royal Society","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000288","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Medical Image Analysis"],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1016\/j.media.2026.103999","type":"journal-article","created":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T00:13:10Z","timestamp":1771891990000},"page":"103999","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"special_numbering":"C","title":["Explicit differentiable slicing and global deformation for cardiac mesh reconstruction"],"prefix":"10.1016","volume":"111","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-1169-2930","authenticated-orcid":false,"given":"Yihao","family":"Luo","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dario","family":"Sesia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5491-8333","authenticated-orcid":false,"given":"Fanwen","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yinzhe","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9665-7933","authenticated-orcid":false,"given":"Wenhao","family":"Ding","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kamrul","family":"Hasan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8032-9097","authenticated-orcid":false,"given":"Jiahao","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fadong","family":"Shi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anoop","family":"Shah","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amit","family":"Kaura","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jamil","family":"Mayet","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7344-7733","authenticated-orcid":false,"given":"Guang","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2918-3077","authenticated-orcid":false,"given":"Choon Hwai","family":"Yap","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.media.2026.103999_bib0001","series-title":"Rotations, Quaternions, and Double Groups","author":"Altmann","year":"2005"},{"issue":"2","key":"10.1016\/j.media.2026.103999_bib0002","doi-asserted-by":"crossref","first-page":"222","DOI":"10.1007\/s10851-008-0135-9","article-title":"A fast and log-euclidean polyaffine framework for locally linear registration","volume":"33","author":"Arsigny","year":"2009","journal-title":"J. Math. Imaging Vis."},{"issue":"2","key":"10.1016\/j.media.2026.103999_bib0003","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1002\/mrm.20965","article-title":"Log-euclidean metrics for fast and simple calculus on diffusion tensors","volume":"56","author":"Arsigny","year":"2006","journal-title":"Mag. Reson. Med. Off. J. Int. Soc. Magn. Reson. Med."},{"issue":"1","key":"10.1016\/j.media.2026.103999_bib0004","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1016\/j.media.2015.08.009","article-title":"A bi-ventricular cardiac atlas built from 1000+ high resolution MR images of healthy subjects and an analysis of shape and motion","volume":"26","author":"Bai","year":"2015","journal-title":"Med. Image Anal."},{"issue":"1","key":"10.1016\/j.media.2026.103999_bib0005","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1186\/s12968-018-0471-x","article-title":"Automated cardiovascular magnetic resonance image analysis with fully convolutional networks","volume":"20","author":"Bai","year":"2018","journal-title":"J. Cardiovasc. Mag. Reson."},{"key":"10.1016\/j.media.2026.103999_bib0006","series-title":"International Workshop on Statistical Atlases and Computational Models of the Heart","first-page":"245","article-title":"Mesh U-Nets for 3D cardiac deformation modeling","author":"Beetz","year":"2022"},{"key":"10.1016\/j.media.2026.103999_bib0007","series-title":"2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)","first-page":"105","article-title":"Biventricular surface reconstruction from cine MRI contours using point completion networks","author":"Beetz","year":"2021"},{"key":"10.1016\/j.media.2026.103999_bib0008","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2023.102975","article-title":"Multi-class point cloud completion networks for 3d cardiac anatomy reconstruction from cine magnetic resonance images","volume":"90","author":"Beetz","year":"2023","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.media.2026.103999_bib0009","doi-asserted-by":"crossref","DOI":"10.3389\/fcvm.2022.983868","article-title":"Interpretable cardiac anatomy modeling using variational mesh autoencoders","volume":"9","author":"Beetz","year":"2022","journal-title":"Frontiers Cardiovasc. Med."},{"issue":"11","key":"10.1016\/j.media.2026.103999_bib0010","doi-asserted-by":"crossref","first-page":"2514","DOI":"10.1109\/TMI.2018.2837502","article-title":"Deep learning techniques for automatic MRI cardiac multi-structures segmentation and diagnosis: is the problem solved?","volume":"37","author":"Bernard","year":"2018","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"4","key":"10.1016\/j.media.2026.103999_bib0011","doi-asserted-by":"crossref","first-page":"1649","DOI":"10.1007\/s11845-022-03210-8","article-title":"Myocardial strain: a clinical review","volume":"192","author":"Brady","year":"2023","journal-title":"Irish J. Med. Sci. (1971-)"},{"issue":"4","key":"10.1016\/j.media.2026.103999_bib0012","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1109\/MSP.2017.2693418","article-title":"Geometric deep learning: going beyond euclidean data","volume":"34","author":"Bronstein","year":"2017","journal-title":"IEEE Signal Process. Mag."},{"key":"10.1016\/j.media.2026.103999_bib0013","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1016\/j.compbiomed.2018.03.013","article-title":"A statistical shape model of the left ventricle from real-time 3D echocardiography and its application to myocardial segmentation of cardiac magnetic resonance images","volume":"96","author":"Carminati","year":"2018","journal-title":"Comput. Biol. Med."},{"key":"10.1016\/j.media.2026.103999_bib0014","series-title":"Information Processing in Medical Imaging (IPMI)","first-page":"333","article-title":"Shape modeling and analysis with entropy-based particle systems","author":"Cates","year":"2007"},{"key":"10.1016\/j.media.2026.103999_bib0015","series-title":"International Workshop on Machine Learning in Medical Imaging","first-page":"150","article-title":"Anatomy-aware cardiac motion estimation","author":"Chen","year":"2020"},{"key":"10.1016\/j.media.2026.103999_bib0016","series-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)","first-page":"327","article-title":"Learning anatomical shape representations with a geometric latent space regularizer","author":"Chen","year":"2019"},{"issue":"3","key":"10.1016\/j.media.2026.103999_bib0017","doi-asserted-by":"crossref","first-page":"218","DOI":"10.1007\/BF01428050","article-title":"Winding numbers on surfaces, i","volume":"196","author":"Chillingworth","year":"1972","journal-title":"Math. Ann."},{"key":"10.1016\/j.media.2026.103999_bib0018","doi-asserted-by":"crossref","first-page":"226","DOI":"10.1016\/j.media.2019.07.006","article-title":"Unsupervised learning for fast probabilistic diffeomorphic registration","volume":"57","author":"Dalca","year":"2019","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.media.2026.103999_bib0019","series-title":"Computational Geometry: Algorithms and Applications","author":"De Berg","year":"2000"},{"key":"10.1016\/j.media.2026.103999_bib0020","article-title":"Physics-informed neural networks for cardiac mechanics modeling: progress and challenges","volume":"399","author":"Dutta","year":"2022","journal-title":"Comput. Methods Appl. Mech. Eng."},{"key":"10.1016\/j.media.2026.103999_bib0021","first-page":"2002","article-title":"Triangulation by ear clipping","author":"Eberly","year":"2008","journal-title":"Geometric Tools"},{"key":"10.1016\/j.media.2026.103999_bib0022","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","first-page":"605","article-title":"A point set generation network for 3D object reconstruction from a single image","author":"Fan","year":"2017"},{"issue":"4","key":"10.1016\/j.media.2026.103999_bib0023","doi-asserted-by":"crossref","DOI":"10.1002\/cnm.3435","article-title":"Polygonal surface processing and mesh generation tools for the numerical simulation of the cardiac function","volume":"37","author":"Fedele","year":"2021","journal-title":"Int. J. Numer. Method Biomed. Eng."},{"issue":"9","key":"10.1016\/j.media.2026.103999_bib0024","doi-asserted-by":"crossref","first-page":"1151","DOI":"10.1109\/TMI.2002.804426","article-title":"Automatic construction of multiple-object three-dimensional statistical shape models: application to cardiac modeling","volume":"21","author":"Frangi","year":"2002","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.media.2026.103999_bib0025","doi-asserted-by":"crossref","DOI":"10.3389\/fphys.2021.679076","article-title":"Pod-enhanced deep learning-based reduced order models for the real-time simulation of cardiac electrophysiology in the left atrium","volume":"12","author":"Fresca","year":"2021","journal-title":"Front. Physiol."},{"key":"10.1016\/j.media.2026.103999_bib0026","unstructured":"Gaggion, N., Matheson, B. A., Xia, Y., Bonazzola, R., Ravikumar, N., Taylor, Z. A., Milone, D. H., Frangi, A. F., Ferrante, E., 2023. Multi-view hybrid graph convolutional network for volume-to-mesh reconstruction in cardiovascular MRI. arXiv: 2311.13706."},{"key":"10.1016\/j.media.2026.103999_bib0027","series-title":"Theoria Attractionis Corporum Sphaeroidicorum Ellipticorum Homogeneorum: Methodo Nova Tractata","author":"Gauss","year":"1877"},{"issue":"4","key":"10.1016\/j.media.2026.103999_bib0028","doi-asserted-by":"crossref","first-page":"663","DOI":"10.1113\/JP285475","article-title":"Pre-intervention myocardial stress is a good predictor of aortic valvoluplasty outcome for fetal critical aortic stenosis and evolving HLHS","volume":"602","author":"Green","year":"2024","journal-title":"J. Physiol."},{"issue":"9","key":"10.1016\/j.media.2026.103999_bib0029","doi-asserted-by":"crossref","first-page":"1027","DOI":"10.1016\/j.cviu.2013.01.014","article-title":"Graph cut segmentation with a statistical shape model in cardiac MRI","volume":"117","author":"Grosgeorge","year":"2013","journal-title":"Comput. Vis. Image Understanding"},{"issue":"1","key":"10.1016\/j.media.2026.103999_bib0030","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1510\/icvts.2005.108555","article-title":"Finite element method in cardiac surgery","volume":"5","author":"Hashim","year":"2006","journal-title":"Interact. Cardiovasc. Thorac. Surg."},{"key":"10.1016\/j.media.2026.103999_bib0031","unstructured":"Hattori, S., Yatagawa, T., Ohtake, Y., Suzuki, H., 2021. Deep mesh prior: Unsupervised mesh restoration using graph convolutional networks. arXiv: 2107.02909."},{"key":"10.1016\/j.media.2026.103999_bib0032","unstructured":"Head, K., 2003. Gravity for beginners."},{"issue":"4","key":"10.1016\/j.media.2026.103999_bib0033","doi-asserted-by":"crossref","first-page":"543","DOI":"10.1016\/j.media.2009.05.004","article-title":"Statistical shape models for 3d medical image segmentation: a review","volume":"13","author":"Heimann","year":"2009","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.media.2026.103999_bib0034","unstructured":"Hendrycks, D., Gimpel, K., 2016. Gaussian error linear units (gelus). arXiv: 1606.08415."},{"key":"10.1016\/j.media.2026.103999_bib0035","series-title":"Proceedings of the 19th Annual Conference on Computer Graphics and Interactive Techniques","first-page":"71","article-title":"Surface reconstruction from unorganized points","author":"Hoppe","year":"1992"},{"key":"10.1016\/j.media.2026.103999_bib0036","series-title":"Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges: 9th International Workshop, STACOM 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers 9","first-page":"221","article-title":"Automatically segmenting the left atrium from cardiac images using successive 3D U-Nets and a contour loss","author":"Jia","year":"2019"},{"key":"10.1016\/j.media.2026.103999_bib0037","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2022.102445","article-title":"Rapid inference of personalised left-ventricular meshes by deformation-based differentiable mesh voxelization","volume":"79","author":"Joyce","year":"2022","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.media.2026.103999_bib0038","unstructured":"Kingma, D. P., Ba, J., 2014. Adam: a method for stochastic optimization. arXiv: 1412.6980."},{"key":"10.1016\/j.media.2026.103999_bib0039","unstructured":"Kingma, D. P., Welling, M., 2013. Auto-encoding variational bayes. arXiv: 1312.6114."},{"key":"10.1016\/j.media.2026.103999_bib0040","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2021.102222","article-title":"A deep-learning approach for direct whole-heart mesh reconstruction","volume":"74","author":"Kong","year":"2021","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.media.2026.103999_bib0041","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","first-page":"2916","article-title":"Deep marching cubes: learning explicit surface representations","author":"Liao","year":"2018"},{"key":"10.1016\/j.media.2026.103999_bib0042","series-title":"Seminal Graphics: Pioneering Efforts That Shaped the Field","first-page":"347","article-title":"Marching cubes: a high resolution 3d surface construction algorithm","author":"Lorensen","year":"1998"},{"key":"10.1016\/j.media.2026.103999_bib0043","series-title":"Proceedings 14th IEEE Symposium on Computer-based Medical Systems. CBMS 2001","first-page":"381","article-title":"Medical image processing, analysis and visualization in clinical research","author":"McAuliffe","year":"2001"},{"key":"10.1016\/j.media.2026.103999_bib0044","article-title":"DeepMesh: mesh-based cardiac motion tracking using deep learning","author":"Meng","year":"2023","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.media.2026.103999_bib0045","series-title":"Visualization and Mathematics III","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1007\/978-3-662-05105-4_2","article-title":"Discrete differential-geometry operators for triangulated 2-manifolds","author":"Meyer","year":"2003"},{"key":"10.1016\/j.media.2026.103999_bib0046","series-title":"2016 Fourth International Conference on 3D Vision (3DV)","first-page":"565","article-title":"V-Net: fully convolutional neural networks for volumetric medical image segmentation","author":"Milletari","year":"2016"},{"key":"10.1016\/j.media.2026.103999_bib0047","series-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)","first-page":"719","article-title":"Fast shape-constrained surface reconstruction from sparse landmarks with variational autoencoders","author":"Mok","year":"2020"},{"issue":"7","key":"10.1016\/j.media.2026.103999_bib0048","doi-asserted-by":"crossref","DOI":"10.1115\/1.4064527","article-title":"LinFlo-Net: a two-stage deep learning method to generate simulation ready meshes of the heart","volume":"146","author":"Narayanan","year":"2024","journal-title":"J. Biomech. Eng."},{"key":"10.1016\/j.media.2026.103999_bib0049","series-title":"Proceedings of the 4th International Conference on Computer Graphics and Interactive Techniques in Australasia and Southeast Asia","first-page":"381","article-title":"Laplacian mesh optimization","author":"Nealen","year":"2006"},{"issue":"6","key":"10.1016\/j.media.2026.103999_bib0050","article-title":"Accuracy of left ventricular cavity volume and ejection fraction for conventional estimation methods and 3D surface fitting","volume":"8","author":"O\u2019Dell","year":"2019","journal-title":"J. Am. Heart Assoc."},{"key":"10.1016\/j.media.2026.103999_bib0051","series-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)","first-page":"643","article-title":"Abdominal multi-organ segmentation with organ-attention networks and statistical fusion","author":"Okada","year":"2015"},{"key":"10.1016\/j.media.2026.103999_bib0052","article-title":"Deep learning-based cardiac computed tomography for quantification of left ventricular function and scar","author":"Otaki","year":"2023","journal-title":"JACC: Cardiovasc. Imaging"},{"key":"10.1016\/j.media.2026.103999_bib0053","series-title":"Information Processing in Medical Imaging: 27th International Conference, IPMI 2021, Virtual Event, June 28\u2013June 30, 2021, Proceedings 27","first-page":"637","article-title":"Weakly supervised deep learning for aortic valve finite element mesh generation from 3D CT images","author":"Pak","year":"2021"},{"issue":"1","key":"10.1016\/j.media.2026.103999_bib0054","article-title":"Uk biobank\u2019s cardiovascular magnetic resonance protocol","volume":"18","author":"Petersen","year":"2016","journal-title":"J. Cardiovasc. Mag. Reson."},{"key":"10.1016\/j.media.2026.103999_bib0055","doi-asserted-by":"crossref","first-page":"787","DOI":"10.1007\/s00371-008-0260-x","article-title":"Spectral mesh deformation","volume":"24","author":"Rong","year":"2008","journal-title":"Vis. Comput."},{"key":"10.1016\/j.media.2026.103999_bib0056","series-title":"Symposium on Geometry Processing","first-page":"225","article-title":"Laplace-Beltrami eigenfunctions for deformation invariant shape representation","volume":"257","author":"Rustamov","year":"2007"},{"key":"10.1016\/j.media.2026.103999_bib0057","series-title":"2013 IEEE International Conference on Acoustics, Speech and Signal Processing","first-page":"6167","article-title":"Discrete signal processing on graphs: graph fourier transform","author":"Sandryhaila","year":"2013"},{"issue":"4","key":"10.1016\/j.media.2026.103999_bib0058","doi-asserted-by":"crossref","DOI":"10.1145\/3592430","article-title":"Flexible isosurface extraction for gradient-based mesh optimization","volume":"42","author":"Shen","year":"2023","journal-title":"ACM Trans. Graph."},{"issue":"3","key":"10.1016\/j.media.2026.103999_bib0059","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1109\/MSP.2012.2235192","article-title":"The emerging field of signal processing on graphs: extending high-dimensional data analysis to networks and other irregular domains","volume":"30","author":"Shuman","year":"2013","journal-title":"IEEE Signal Process. Mag."},{"key":"10.1016\/j.media.2026.103999_bib0060","doi-asserted-by":"crossref","first-page":"82031","DOI":"10.1109\/ACCESS.2021.3086020","article-title":"U-Net and its variants for medical image segmentation: a review of theory and applications","volume":"9","author":"Siddique","year":"2021","journal-title":"IEEE Access"},{"key":"10.1016\/j.media.2026.103999_bib0061","series-title":"2024 IEEE International Symposium on Biomedical Imaging (ISBI)","first-page":"1","article-title":"Intensity-based 3D motion correction for cardiac MR images","author":"Stolt-Ans\u00f3","year":"2024"},{"issue":"2","key":"10.1016\/j.media.2026.103999_bib0062","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1109\/JBHI.2017.2652449","article-title":"Statistical shape modeling of the left ventricle: myocardial infarct classification challenge","volume":"22","author":"Suinesiaputra","year":"2017","journal-title":"IEEE J. Biomed. Health Inf."},{"key":"10.1016\/j.media.2026.103999_bib0063","series-title":"The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","article-title":"TopNet: structural point cloud decoder","author":"Tchapmi","year":"2019"},{"key":"10.1016\/j.media.2026.103999_bib0064","series-title":"Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges: 8th International Workshop, STACOM 2017, Held in Conjunction with MICCAI 2017, Quebec City, Canada, September 10\u201314, 2017, Revised Selected Papers 8","first-page":"224","article-title":"3D deeply-supervised U-Net based whole heart segmentation","author":"Tong","year":"2018"},{"key":"10.1016\/j.media.2026.103999_bib0065","series-title":"International Conference on Functional Imaging and Modeling of the Heart","first-page":"253","article-title":"CNN-based cardiac motion extraction to generate deformable geometric left ventricle myocardial models from cine mri","author":"Upendra","year":"2021"},{"key":"10.1016\/j.media.2026.103999_bib0066","series-title":"Electromagnetic Fields","volume":"Vol. 19","author":"Van Bladel","year":"2007"},{"issue":"1","key":"10.1016\/j.media.2026.103999_bib0067","doi-asserted-by":"crossref","DOI":"10.3390\/jimaging4010016","article-title":"Surface mesh reconstruction from cardiac MRI contours","volume":"4","author":"Villard","year":"2018","journal-title":"J. Imaging"},{"issue":"5","key":"10.1016\/j.media.2026.103999_bib0068","doi-asserted-by":"crossref","DOI":"10.1148\/ryct.2019190034","article-title":"Left ventricular mid-diastolic wall thickness: normal values for coronary CT angiography","volume":"1","author":"Walpot","year":"2019","journal-title":"Radiol. Cardiothorac. Imaging"},{"key":"10.1016\/j.media.2026.103999_bib0069","article-title":"Neural implicit surface reconstruction for medical images","author":"Wang","year":"2024","journal-title":"Med. Image Anal."},{"issue":"1","key":"10.1016\/j.media.2026.103999_bib0070","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1109\/TNNLS.2020.2978386","article-title":"A comprehensive survey on graph neural networks","volume":"32","author":"Wu","year":"2020","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"16","key":"10.1016\/j.media.2026.103999_bib0071","doi-asserted-by":"crossref","first-page":"e147","DOI":"10.1016\/j.jacc.2013.05.019","article-title":"2013\u202fACCF\/AHA Guideline for the management of heart failure: a report of the american college of cardiology foundation\/american heart association task force on practice guidelines","volume":"62","author":"Yancy","year":"2013","journal-title":"J. Am. Coll. Cardiol."},{"key":"10.1016\/j.media.2026.103999_bib0072","series-title":"Computer Graphics Forum","first-page":"1865","article-title":"Spectral mesh processing","volume":"29","author":"Zhang","year":"2010"},{"key":"10.1016\/j.media.2026.103999_bib0073","doi-asserted-by":"crossref","DOI":"10.3389\/fcvm.2022.1016703","article-title":"MITEA: a dataset for machine learning segmentation of the left ventricle in 3D echocardiography using subject-specific labels from cardiac magnetic resonance imaging","volume":"9","author":"Zhao","year":"2023","journal-title":"Front. Cardiovasc. Med."},{"key":"10.1016\/j.media.2026.103999_bib0074","series-title":"Thirty-seventh Conference on Neural Information Processing Systems","article-title":"Michelangelo: conditional 3D shape generation based on shape-image-text aligned latent representation","author":"Zhao","year":"2023"},{"key":"10.1016\/j.media.2026.103999_bib0075","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2019.101537","article-title":"Evaluation of algorithms for multi-modality whole heart segmentation: an open-access grand challenge","volume":"58","author":"Zhuang","year":"2019","journal-title":"Med. Image Anal."}],"container-title":["Medical Image Analysis"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S136184152600068X?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S136184152600068X?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T00:07:01Z","timestamp":1778803621000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S136184152600068X"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6]]},"references-count":75,"alternative-id":["S136184152600068X"],"URL":"https:\/\/doi.org\/10.1016\/j.media.2026.103999","relation":{},"ISSN":["1361-8415"],"issn-type":[{"value":"1361-8415","type":"print"}],"subject":[],"published":{"date-parts":[[2026,6]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Explicit differentiable slicing and global deformation for cardiac mesh reconstruction","name":"articletitle","label":"Article Title"},{"value":"Medical Image Analysis","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.media.2026.103999","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Authors. Published by Elsevier B.V.","name":"copyright","label":"Copyright"}],"article-number":"103999"}}