{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T07:45:41Z","timestamp":1785829541700,"version":"3.56.0"},"reference-count":64,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T00:00:00Z","timestamp":1784160000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001516","name":"Heart Foundation of New Zealand","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001516","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001505","name":"Health Research Council of New Zealand","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001505","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":[[2026,9]]},"DOI":"10.1016\/j.media.2026.104223","type":"journal-article","created":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T12:24:03Z","timestamp":1784204643000},"page":"104223","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Spatial phenotyping of epicardial adipose tissue from cardiac MRI"],"prefix":"10.1016","volume":"113","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-6382-1596","authenticated-orcid":false,"given":"Fan","family":"Feng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ting","family":"Long","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abdallah I.","family":"Hasaballa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinyi","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yun","family":"Gu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2198-9690","authenticated-orcid":false,"given":"Carl-Johan","family":"Carlh\u00e4ll","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3303-0401","authenticated-orcid":false,"given":"Jichao","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.media.2026.104223_bib0001","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1016\/j.ejrad.2005.12.030","article-title":"Mapping epicardial fat with multi-detector computed tomography to facilitate percutaneous transepicardial arrhythmia ablation","volume":"57","author":"Abbara","year":"2006","journal-title":"Eur. J. Radiol."},{"key":"10.1016\/j.media.2026.104223_bib0002","doi-asserted-by":"crossref","DOI":"10.1093\/europace\/euaf134","article-title":"Regionalization of the atria for 3D electroanatomical mapping, cardiac imaging, and computational modelling: a clinical consensus statement of the european heart rhythm association and the european association of cardiovascular imaging of the ESC","volume":"27","author":"Althoff","year":"2025","journal-title":"Europace"},{"key":"10.1016\/j.media.2026.104223_bib0003","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1111\/j.1538-4632.1995.tb00338.x","article-title":"Local indicators of spatial association\u2014LISA","volume":"27","author":"Anselin","year":"1995","journal-title":"Geogr. Anal."},{"key":"10.1016\/j.media.2026.104223_bib0004","doi-asserted-by":"crossref","first-page":"3827","DOI":"10.1093\/eurheartj\/ehad484","article-title":"Perivascular adipose tissue as a source of therapeutic targets and clinical biomarkers","volume":"44","author":"Antoniades","year":"2023","journal-title":"Eur. Heart J."},{"key":"10.1016\/j.media.2026.104223_bib0005","first-page":"230","article-title":"Left atrial epicardial adiposity and atrial fibrillation","volume":"3","author":"Batal","year":"2010","journal-title":"Circ: Arrhythmia Electrophysiol."},{"key":"10.1016\/j.media.2026.104223_bib0006","doi-asserted-by":"crossref","first-page":"645","DOI":"10.1111\/joim.12384","article-title":"The swedish CArdioPulmonary BioImage study: objectives and design","volume":"278","author":"Bergstr\u00f6m","year":"2015","journal-title":"J. Intern. Med."},{"key":"10.1016\/j.media.2026.104223_bib0007","article-title":"The epicardial adipose tissue confined in the atrioventricular groove can be used to assess atrial adipose tissue and atrial dysfunction in cardiac magnetic resonance imaging","volume":"2","author":"Bialobroda","year":"2024","journal-title":"Eur. Heart J. - Imaging Methods Pract."},{"key":"10.1016\/j.media.2026.104223_bib0008","unstructured":"Cardoso, M.J., Li, W., Brown, R., Ma, N., Kerfoot, E., Wang, Y., Murrey, B., Myronenko, A., Zhao, C., Yang, D., Nath, V., He, Y., Xu, Z., Hatamizadeh, A., Myronenko, A., Zhu, W., Liu, Y., Zheng, M., Tang, Y., Yang, I., Zephyr, M., Hashemian, B., Alle, S., Darestani, M.Z., Budd, C., Modat, M., Vercauteren, T., Wang, G., Li, Y., Hu, Y., Fu, Y., Gorman, B., Johnson, H., Genereaux, B., Erdal, B.S., Gupta, V., Diaz-Pinto, A., Dourson, A., Maier-Hein, L., Jaeger, P.F., Baumgartner, M., Kalpathy-Cramer, J., Flores, M., Kirby, J., Cooper, L.A.D., Roth, H.R., Xu, D., Bericat, D., Floca, R., Zhou, S.K., Shuaib, H., Farahani, K., Maier-Hein, K.H., Aylward, S., Dogra, P., Ourselin, S., Feng, A., 2022. MONAI: an open-source framework for deep learning in healthcare. https:\/\/doi.org\/10.48550\/arXiv.2211.02701."},{"key":"10.1016\/j.media.2026.104223_bib0009","doi-asserted-by":"crossref","first-page":"539","DOI":"10.1161\/hc0402.102975","article-title":"Standardized myocardial segmentation and nomenclature for tomographic imaging of the heart: a statement for healthcare professionals from the cardiac imaging committee of the council on clinical cardiology of the american heart association","volume":"105","author":"Cerqueira","year":"2002","journal-title":"Circulation"},{"key":"10.1016\/j.media.2026.104223_bib0010","doi-asserted-by":"crossref","DOI":"10.1093\/europace\/euae258","article-title":"Atrial fibrillation substrate and impaired left atrial function: a cardiac MRI study","volume":"26","author":"Chahine","year":"2024","journal-title":"Europace"},{"key":"10.1016\/j.media.2026.104223_bib0011","doi-asserted-by":"crossref","first-page":"2386","DOI":"10.1109\/TMI.2023.3251368","article-title":"Segmentation of pericardial adipose tissue in CMR images: a benchmark dataset MRPEAT and a triple-stage network 3SUnet","volume":"42","author":"Chen","year":"2023","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.media.2026.104223_bib0012","article-title":"Epicardial adipose tissue: an emerging biomarker of cardiovascular complications in type 2 diabetes?","volume":"11","author":"Christensen","year":"2020","journal-title":"Ther. Adv. Endocrinol."},{"key":"10.1016\/j.media.2026.104223_bib0013","doi-asserted-by":"crossref","first-page":"1835","DOI":"10.1109\/TMI.2018.2804799","article-title":"Deep learning for quantification of epicardial and thoracic adipose tissue from non-contrast CT","volume":"37","author":"Commandeur","year":"2018","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.media.2026.104223_bib0014","doi-asserted-by":"crossref","DOI":"10.1038\/s44325-025-00065-7","article-title":"Methods to model epicardial adipose tissue-mediated atrial fibrillation","volume":"2","author":"Cook","year":"2025","journal-title":"npj Cardiovasc. Health"},{"key":"10.1016\/j.media.2026.104223_bib0015","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2025.103636","article-title":"XCAT 3.0: a comprehensive library of personalized digital twins derived from CT scans","volume":"103","author":"Dahal","year":"2025","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.media.2026.104223_bib0016","series-title":"Presented at the Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"4336","article-title":"Fast local thickness","author":"Dahl","year":"2023"},{"key":"10.1016\/j.media.2026.104223_bib0017","doi-asserted-by":"crossref","first-page":"126","DOI":"10.3390\/diagnostics12010126","article-title":"Deep-learning segmentation of epicardial adipose tissue using four-chamber cardiac magnetic resonance imaging","volume":"12","author":"Daud\u00e9","year":"2022","journal-title":"Diagnostics"},{"key":"10.1016\/j.media.2026.104223_bib0018","doi-asserted-by":"crossref","DOI":"10.3389\/fcvm.2022.813427","article-title":"Ectopic fat is associated with cardiac remodeling\u2014a comprehensive assessment of regional fat depots in type 2 diabetes using multi-parametric MRI","volume":"9","author":"Edin","year":"2022","journal-title":"Front. Cardiovasc. Med."},{"key":"10.1016\/j.media.2026.104223_bib0019","doi-asserted-by":"crossref","first-page":"1471","DOI":"10.1002\/mrm.28022","article-title":"FatSegNet: a fully automated deep learning pipeline for adipose tissue segmentation on abdominal dixon MRI","volume":"83","author":"Estrada","year":"2020","journal-title":"Magn. Reson. Med."},{"key":"10.1016\/j.media.2026.104223_bib0020","doi-asserted-by":"crossref","first-page":"294","DOI":"10.1186\/s12933-025-02829-y","article-title":"AI-driven segmentation and morphogeometric profiling of epicardial adipose tissue in type 2 diabetes","volume":"24","author":"Feng","year":"2025","journal-title":"Cardiovasc. Diabetol."},{"key":"10.1016\/j.media.2026.104223_bib0021","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-025-10110-1","article-title":"Poincare guided geometric UNet for left atrial epicardial adipose tissue segmentation in Dixon MRI images","volume":"15","author":"Firouznia","year":"2025","journal-title":"Sci. Rep."},{"key":"10.1016\/j.media.2026.104223_bib0022","doi-asserted-by":"crossref","DOI":"10.1161\/JAHA.113.000582","article-title":"Epicardial and perivascular adipose tissues and their influence on cardiovascular disease: basic mechanisms and clinical associations","volume":"3","author":"Fitzgibbons","year":"2014","journal-title":"JAHA"},{"key":"10.1016\/j.media.2026.104223_bib0023","doi-asserted-by":"crossref","first-page":"870","DOI":"10.1038\/oby.2007.591","article-title":"Volumetric assessment of epicardial adipose tissue with cardiovascular magnetic resonance imaging","volume":"15","author":"Fl\u00fcchter","year":"2007","journal-title":"Obesity"},{"key":"10.1016\/j.media.2026.104223_bib0024","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1093\/cvr\/cvv208","article-title":"Human epicardial adipose tissue has a specific transcriptomic signature depending on its anatomical peri-atrial, peri-ventricular, or peri-coronary location","volume":"108","author":"Gaborit","year":"2015","journal-title":"Cardiovasc. Res."},{"key":"10.1016\/j.media.2026.104223_bib0025","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1186\/s12933-025-02946-8","article-title":"AI-quantified epicardial adipose tissue and prediction of future myocardial infarction in patients with cardiometabolic disease: a post-hoc analysis from the SCOT-HEART trial","volume":"24","author":"Geers","year":"2025","journal-title":"Cardiovasc. Diabetol."},{"key":"10.1016\/j.media.2026.104223_bib0026","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1111\/j.1538-4632.1992.tb00261.x","article-title":"The analysis of spatial association by use of distance statistics","volume":"24","author":"Getis","year":"1992","journal-title":"Geogr. Anal."},{"key":"10.1016\/j.media.2026.104223_bib0027","doi-asserted-by":"crossref","first-page":"2324","DOI":"10.1161\/CIRCULATIONAHA.111.039586","article-title":"Secretory products from epicardial adipose tissue of patients with type 2 diabetes mellitus induce cardiomyocyte dysfunction","volume":"126","author":"Greulich","year":"2012","journal-title":"Circulation"},{"key":"10.1016\/j.media.2026.104223_bib0028","first-page":"435","article-title":"Differences in the structural characteristics and distribution of epicardial adipose tissue between left and right atrial fibrillation","volume":"20","author":"Hasebe","year":"2018","journal-title":"EP Eur."},{"key":"10.1016\/j.media.2026.104223_bib0029","doi-asserted-by":"crossref","unstructured":"Hatamizadeh, A., Nath, V., Tang, Y., Yang, D., Roth, H., Xu, D., 2022. Swin UNETR: swin transformers for semantic segmentation of brain tumors in MRI images. https:\/\/doi.org\/10.48550\/arXiv.2201.01266.","DOI":"10.1007\/978-3-031-08999-2_22"},{"key":"10.1016\/j.media.2026.104223_bib0030","doi-asserted-by":"crossref","unstructured":"Hatamizadeh, A., Tang, Y., Nath, V., Yang, D., Myronenko, A., Landman, B., Roth, H., Xu, D., 2021. UNETR: transformers for 3D medical image segmentation. https:\/\/doi.org\/10.48550\/arXiv.2103.10504.","DOI":"10.1109\/WACV51458.2022.00181"},{"key":"10.1016\/j.media.2026.104223_bib0031","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1093\/cvr\/cvu045","article-title":"Epicardial adipose tissue and atrial fibrillation","volume":"102","author":"Hatem","year":"2014","journal-title":"Cardiovasc. Res."},{"key":"10.1016\/j.media.2026.104223_bib0032","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1186\/s12880-020-00478-z","article-title":"Quantification of epicardial fat using 3D cine Dixon MRI","volume":"20","author":"Henningsson","year":"2020","journal-title":"BMC Med. ImAging"},{"key":"10.1016\/j.media.2026.104223_bib0033","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1007\/s10554-015-0778-8","article-title":"3D-Dixon MRI based volumetry of peri- and epicardial fat","volume":"32","author":"Homsi","year":"2016","journal-title":"Int. J. Cardiovasc. ImAging"},{"key":"10.1016\/j.media.2026.104223_bib0034","series-title":"2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). Presented at the 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","first-page":"3938","article-title":"Automatic deep learning segmentation and quantification of epicardial adipose tissue in non-contrast cardiac CT scans","author":"Hoori","year":"2021"},{"key":"10.1016\/j.media.2026.104223_bib0035","article-title":"Artificial intelligence prediction of cardiovascular events using opportunistic epicardial adipose tissue assessments from computed tomography calcium score","volume":"3","author":"Hu","year":"2024","journal-title":"JACC: Adv."},{"key":"10.1016\/j.media.2026.104223_bib0036","doi-asserted-by":"crossref","first-page":"363","DOI":"10.1038\/nrendo.2015.58","article-title":"Local and systemic effects of the multifaceted epicardial adipose tissue depot","volume":"11","author":"Iacobellis","year":"2015","journal-title":"Nat. Rev. Endocrinol."},{"key":"10.1016\/j.media.2026.104223_bib0037","doi-asserted-by":"crossref","first-page":"593","DOI":"10.1038\/s41569-022-00679-9","article-title":"Epicardial adipose tissue in contemporary cardiology","volume":"19","author":"Iacobellis","year":"2022","journal-title":"Nat. Rev. Cardiol."},{"key":"10.1016\/j.media.2026.104223_bib0038","doi-asserted-by":"crossref","first-page":"450","DOI":"10.1016\/j.tem.2011.07.003","article-title":"Epicardial adipose tissue: emerging physiological, pathophysiological and clinical features","volume":"22","author":"Iacobellis","year":"2011","journal-title":"Trends Endocrinol. Metab."},{"key":"10.1016\/j.media.2026.104223_bib0039","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1038\/s41592-020-01008-z","article-title":"nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation","volume":"18","author":"Isensee","year":"2021","journal-title":"Nat. Methods"},{"key":"10.1016\/j.media.2026.104223_bib0040","doi-asserted-by":"crossref","first-page":"860","DOI":"10.1093\/cvr\/cvaf056","article-title":"The role of epicardial adipose tissue remodelling in heart failure with preserved ejection fraction","volume":"121","author":"Janssen-Telders","year":"2025","journal-title":"Cardiovasc. Res."},{"key":"10.1016\/j.media.2026.104223_bib0041","series-title":"2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). Presented at the 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","first-page":"3933","article-title":"3D Neural networks for visceral and subcutaneous adipose tissue segmentation using volumetric Multi-Contrast MRI","author":"Kafali","year":"2021"},{"key":"10.1016\/j.media.2026.104223_bib0042","series-title":"Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges, Lecture Notes in Computer Science","first-page":"371","article-title":"Left-ventricle quantification using residual U-net","author":"Kerfoot","year":"2019"},{"key":"10.1016\/j.media.2026.104223_bib0043","doi-asserted-by":"crossref","first-page":"406","DOI":"10.1016\/j.jjcc.2015.11.005","article-title":"Inflammation of left atrial epicardial adipose tissue is associated with paroxysmal atrial fibrillation","volume":"68","author":"Kusayama","year":"2016","journal-title":"J. Cardiol."},{"key":"10.1016\/j.media.2026.104223_bib0044","article-title":"Fully automated and standardized segmentation of adipose tissue compartments via deep learning in 3D whole-body MRI of epidemiologic cohort studies","volume":"2","author":"K\u00fcstner","year":"2020","journal-title":"Radiol.: Artif. Intell."},{"key":"10.1016\/j.media.2026.104223_bib0045","doi-asserted-by":"crossref","first-page":"2736","DOI":"10.1002\/mrm.27550","article-title":"Fully convolutional networks for automated segmentation of abdominal adipose tissue depots in multicenter water\u2013fat MRI","volume":"81","author":"Langner","year":"2019","journal-title":"Magn. Reson. Med."},{"key":"10.1016\/j.media.2026.104223_bib0046","article-title":"Adipose tissue-endothelial cell interactions in obesity-induced endothelial dysfunction","volume":"8","author":"Li","year":"2021","journal-title":"Front. Cardiovasc. Med."},{"key":"10.1016\/j.media.2026.104223_bib0047","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/j.media.2018.01.004","article-title":"3D multi-scale FCN with random modality voxel dropout learning for intervertebral disc localization and segmentation from multi-modality MR images","volume":"45","author":"Li","year":"2018","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.media.2026.104223_bib0048","doi-asserted-by":"crossref","first-page":"272","DOI":"10.1007\/s00018-022-04286-2","article-title":"Adipokines, adiposity, and atherosclerosis","volume":"79","author":"Liu","year":"2022","journal-title":"Cell. Mol. Life Sci."},{"key":"10.1016\/j.media.2026.104223_bib0049","doi-asserted-by":"crossref","DOI":"10.1016\/j.diabres.2025.112384","article-title":"A review of the relationship between epicardial adipose tissue and cerebral white matter microstructural damage in type 2 diabetes mellitus","volume":"227","author":"Liu","year":"2025","journal-title":"Diabetes Res. Clin. Pract."},{"key":"10.1016\/j.media.2026.104223_bib0050","first-page":"889","article-title":"Fat deposition in dilated cardiomyopathy assessed by CMR","volume":"6","author":"Lu","year":"2013","journal-title":"JACC: Cardiovasc. Imaging"},{"key":"10.1016\/j.media.2026.104223_bib0051","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1186\/1532-429X-15-73","article-title":"Cardiovascular magnetic resonance of total and atrial pericardial adipose tissue: a validation study and development of a 3 dimensional pericardial adipose tissue model","volume":"15","author":"Mahajan","year":"2013","journal-title":"J. Cardiovasc. Magn. Reson."},{"key":"10.1016\/j.media.2026.104223_bib0052","doi-asserted-by":"crossref","first-page":"490","DOI":"10.1093\/ehjci\/jex314","article-title":"Epicardial adipose tissue volume assessed by computed tomography and coronary artery disease: a systematic review and meta-analysis","volume":"19","author":"Mancio","year":"2018","journal-title":"Eur. Heart J. - Cardiovasc. Imaging"},{"key":"10.1016\/j.media.2026.104223_bib0053","doi-asserted-by":"crossref","first-page":"218","DOI":"10.14744\/SEMB.2025.89896","article-title":"Prognostic value of epicardial fat volume quantification related to coronary artery calcium score and degree of stenosis on coronary CT angiography","author":"Mesrur Halefoglu","year":"2025","journal-title":"Sisli Etfal"},{"key":"10.1016\/j.media.2026.104223_bib0054","doi-asserted-by":"crossref","DOI":"10.1259\/bjr.20190770","article-title":"Novel imaging biomarkers: epicardial adipose tissue evaluation","volume":"93","author":"Monti","year":"2020","journal-title":"BJR"},{"key":"10.1016\/j.media.2026.104223_bib0055","doi-asserted-by":"crossref","DOI":"10.1161\/JAHA.117.008232","article-title":"Left atrial epicardial fat volume is associated with atrial fibrillation: a prospective cardiovascular magnetic resonance 3D Dixon study","volume":"7","author":"Nakamori","year":"2018","journal-title":"JAHA"},{"key":"10.1016\/j.media.2026.104223_bib0056","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1186\/s12933-024-02474-x","article-title":"Epicardial fat density obtained with computed tomography imaging - more important than volume?","volume":"23","author":"Nogajski","year":"2024","journal-title":"Cardiovasc. Diabetol."},{"key":"10.1016\/j.media.2026.104223_bib0057","unstructured":"Oktay, O., Schlemper, J., Folgoc, L.L., Lee, M., Heinrich, M., Misawa, K., Mori, K., McDonagh, S., Hammerla, N.Y., Kainz, B., Glocker, B., Rueckert, D., 2018. Attention U-Net: learning where to look for the Pancreas. arXiv preprint arXiv:1804.03999."},{"key":"10.1016\/j.media.2026.104223_bib0058","doi-asserted-by":"crossref","first-page":"286","DOI":"10.1111\/j.1538-4632.1995.tb00912.x","article-title":"Local spatial autocorrelation statistics: distributional issues and an application","volume":"27","author":"Ord","year":"1995","journal-title":"Geogr. Anal."},{"key":"10.1016\/j.media.2026.104223_bib0059","doi-asserted-by":"crossref","first-page":"889","DOI":"10.1007\/s10741-017-9644-1","article-title":"Epicardial adipose tissue as a metabolic transducer: role in heart failure and coronary artery disease","volume":"22","author":"Patel","year":"2017","journal-title":"Heart. Fail. Rev."},{"key":"10.1016\/j.media.2026.104223_bib0060","doi-asserted-by":"crossref","first-page":"907","DOI":"10.1016\/j.ahj.2007.03.019","article-title":"Human epicardial adipose tissue: a review","volume":"153","author":"Sacks","year":"2007","journal-title":"Am. Heart J."},{"key":"10.1016\/j.media.2026.104223_bib0061","doi-asserted-by":"crossref","DOI":"10.1002\/mco2.413","article-title":"Epicardial adipose tissue, metabolic disorders, and cardiovascular diseases: recent advances classified by research methodologies","volume":"4","author":"Song","year":"2023","journal-title":"MedComm"},{"key":"10.1016\/j.media.2026.104223_bib0062","doi-asserted-by":"crossref","DOI":"10.1093\/eurheartj\/ehw045","article-title":"Epicardial fat and atrial fibrillation: current evidence, potential mechanisms, clinical implications, and future directions","author":"Wong","year":"2016","journal-title":"Eur. Heart. J."},{"key":"10.1016\/j.media.2026.104223_bib0063","doi-asserted-by":"crossref","first-page":"398","DOI":"10.1186\/s12872-022-02843-y","article-title":"The correlation of pericoronary adipose tissue with coronary artery disease and left ventricular function","volume":"22","author":"You","year":"2022","journal-title":"BMC Cardiovasc. Disord."},{"key":"10.1016\/j.media.2026.104223_bib0064","series-title":"Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support","first-page":"3","article-title":"UNet++: a nested U-net architecture for medical image segmentation","author":"Zhou","year":"2018"}],"container-title":["Medical Image Analysis"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1361841526002926?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1361841526002926?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T06:54:48Z","timestamp":1785826488000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1361841526002926"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":64,"alternative-id":["S1361841526002926"],"URL":"https:\/\/doi.org\/10.1016\/j.media.2026.104223","relation":{},"ISSN":["1361-8415"],"issn-type":[{"value":"1361-8415","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Spatial phenotyping of epicardial adipose tissue from cardiac MRI","name":"articletitle","label":"Article Title"},{"value":"Medical Image Analysis","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.media.2026.104223","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":"104223"}}