{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,21]],"date-time":"2025-06-21T04:02:43Z","timestamp":1750478563693,"version":"3.41.0"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031945618","type":"print"},{"value":"9783031945625","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-94562-5_10","type":"book-chapter","created":{"date-parts":[[2025,6,20]],"date-time":"2025-06-20T10:06:40Z","timestamp":1750414000000},"page":"98-109","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Integrated Framework for\u00a0Unified Cardiac and\u00a0Vascular Mesh Construction from\u00a0Medical Images"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-6389-6631","authenticated-orcid":false,"given":"Numi","family":"Sveinsson Cepero","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0001-5236-1452","authenticated-orcid":false,"given":"Arjun","family":"Narayanan","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7561-1568","authenticated-orcid":false,"given":"Shawn C.","family":"Shadden","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,5,29]]},"reference":[{"key":"10_CR1","unstructured":"Cignoni, P., Callieri, M., Corsini, M., Dellepiane, M., Ganovelli, F., Ranzuglia, G.: MeshLab: an open-source mesh processing tool. In: Scarano, V., Chiara, R.D., Erra, U. (eds.) Eurographics Italian Chapter Conference. The Eurographics Association (2008). https:\/\/doi.org\/10.2312\/LocalChapterEvents\/ItalChap\/ItalianChapConf2008\/129-136"},{"key":"10_CR2","doi-asserted-by":"publisher","unstructured":"Gray, R.A., Pathmanathan, P.: Patient-specific cardiovascular computational modeling: diversity of personalization and challenges. J. Cardiovasc. Transl. Res. 11(2), 80\u201388 (2018). https:\/\/doi.org\/10.1007\/s12265-018-9792-2","DOI":"10.1007\/s12265-018-9792-2"},{"issue":"2","key":"10_CR3","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1038\/s41592-020-01008-z","volume":"18","author":"F Isensee","year":"2021","unstructured":"Isensee, F., Jaeger, P.F., Kohl, S., Petersen, J., Maier-Hein, K.H.: nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation. Nat. Methods 18(2), 203\u2013211 (2021). https:\/\/doi.org\/10.1038\/s41592-020-01008-z","journal-title":"Nat. Methods"},{"key":"10_CR4","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1016\/j.media.2018.08.004","volume":"50","author":"R Karim","year":"2018","unstructured":"Karim, R., et al.: Algorithms for left atrial wall segmentation and thickness - evaluation on an open-source CT and MRI image database. Med. Image Anal. 50, 36\u201353 (2018). https:\/\/doi.org\/10.1016\/j.media.2018.08.004","journal-title":"Med. Image Anal."},{"key":"10_CR5","doi-asserted-by":"publisher","unstructured":"Kong, F., Shadden, S.C.: Automating model generation for image-based cardiac flow simulation. J. Heat Transf. 142(11) (2020). https:\/\/doi.org\/10.1115\/1.4048032","DOI":"10.1115\/1.4048032"},{"issue":"2","key":"10_CR6","doi-asserted-by":"publisher","first-page":"533","DOI":"10.1109\/TMI.2022.3219284","volume":"42","author":"F Kong","year":"2023","unstructured":"Kong, F., Shadden, S.C.: Learning whole heart mesh generation from patient images for computational simulations. IEEE Trans. Med. Imaging 42(2), 533\u2013545 (2023). https:\/\/doi.org\/10.1109\/TMI.2022.3219284","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10_CR7","doi-asserted-by":"publisher","unstructured":"Kong, F., Wilson, N., Shadden, S.: A deep-learning approach for direct whole-heart mesh reconstruction. Med. Image Anal. 74 (2021). https:\/\/doi.org\/10.1016\/j.media.2021.102222","DOI":"10.1016\/j.media.2021.102222"},{"issue":"4","key":"10_CR8","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1145\/37402.37422","volume":"21","author":"WE Lorensen","year":"1987","unstructured":"Lorensen, W.E., Cline, H.E.: Marching cubes: a high resolution 3D surface construction algorithm. SIGGRAPH Comput. Graph. 21(4), 163\u2013169 (1987). https:\/\/doi.org\/10.1145\/37402.37422","journal-title":"SIGGRAPH Comput. Graph."},{"issue":"2","key":"10_CR9","doi-asserted-by":"publisher","first-page":"104","DOI":"10.1111\/j.1747-0803.2010.00383.x","volume":"5","author":"AL Marsden","year":"2010","unstructured":"Marsden, A.L., Reddy, V.M., Shadden, S.C., Chan, F.P., Taylor, C.A., Feinstein, J.A.: A new multiparameter approach to computational simulation for fontan assessment and redesign. Congenit. Heart Dis. 5(2), 104\u2013117 (2010). https:\/\/doi.org\/10.1111\/j.1747-0803.2010.00383.x","journal-title":"Congenit. Heart Dis."},{"key":"10_CR10","doi-asserted-by":"publisher","unstructured":"Narayanan, A., Kong, F., Shadden, S.: LinFlo-Net: a two-stage deep learning method to generate simulation ready meshes of the heart. J. Biomech. Eng. 146(7) (2024). https:\/\/doi.org\/10.1115\/1.4064527","DOI":"10.1115\/1.4064527"},{"key":"10_CR11","doi-asserted-by":"publisher","unstructured":"Paritala, P.K., et al.: Reproducibility of the computational fluid dynamic analysis of a cerebral aneurysm monitored over a decade. Sci. Rep. 13(1) (2023). https:\/\/doi.org\/10.1038\/s41598-022-27354-w","DOI":"10.1038\/s41598-022-27354-w"},{"key":"10_CR12","doi-asserted-by":"publisher","unstructured":"Schwarz, E.L., Pegolotti, L., Pfaller, M.R., Marsden, A.L.: Beyond CFD: emerging methodologies for predictive simulation in cardiovascular health and disease. Biophys. Rev. 4(1) (2023). https:\/\/doi.org\/10.1063\/5.0109400","DOI":"10.1063\/5.0109400"},{"issue":"1","key":"10_CR13","doi-asserted-by":"publisher","first-page":"158","DOI":"10.1007\/s10439-024-03611-z","volume":"53","author":"N Sveinsson Cepero","year":"2025","unstructured":"Sveinsson Cepero, N., Shadden, S.C.: SeqSeg: learning local segments for automatic vascular model construction. Ann. Biomed. Eng. 53(1), 158\u2013179 (2025). https:\/\/doi.org\/10.1007\/s10439-024-03611-z","journal-title":"Ann. Biomed. Eng."},{"issue":"7","key":"10_CR14","doi-asserted-by":"publisher","first-page":"1460","DOI":"10.1109\/TMI.2015.2398818","volume":"34","author":"C Tobon-Gomez","year":"2015","unstructured":"Tobon-Gomez, C., et al.: Benchmark for algorithms segmenting the left atrium from 3D CT and MRI datasets. IEEE Trans. Med. Imaging 34(7), 1460\u20131473 (2015). https:\/\/doi.org\/10.1109\/TMI.2015.2398818","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10_CR15","doi-asserted-by":"publisher","unstructured":"Wasserthal, J., et al.: TotalSegmentator: robust segmentation of 104 anatomic structures in CT images. Radiol. Artif. Intell. 5(5) (2023). https:\/\/doi.org\/10.5281\/zenodo.6802613","DOI":"10.5281\/zenodo.6802613"},{"issue":"5","key":"10_CR16","doi-asserted-by":"publisher","first-page":"2361","DOI":"10.1118\/1.4945696","volume":"43","author":"JM Wolterink","year":"2016","unstructured":"Wolterink, J.M., et al.: An evaluation of automatic coronary artery calcium scoring methods with cardiac CT using the orCaScore framework. Med. Phys. 43(5), 2361\u20132373 (2016). https:\/\/doi.org\/10.1118\/1.4945696","journal-title":"Med. Phys."},{"key":"10_CR17","doi-asserted-by":"publisher","unstructured":"Zhuang, X., et al.: Evaluation of algorithms for multi-modality whole heart segmentation: an open-access grand challenge. Med. Image Anal. 58 (2019). https:\/\/doi.org\/10.1016\/j.media.2019.101537","DOI":"10.1016\/j.media.2019.101537"}],"container-title":["Lecture Notes in Computer Science","Functional Imaging and Modeling of the Heart"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-94562-5_10","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,20]],"date-time":"2025-06-20T10:06:41Z","timestamp":1750414001000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-94562-5_10"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031945618","9783031945625"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-94562-5_10","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"29 May 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"FIMH","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Functional Imaging and Modeling of the Heart","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Dallas, TX","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"USA","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2 June 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 June 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"fimh2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/fimh2025.sciencesconf.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}