{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T10:25:20Z","timestamp":1760955920649,"version":"3.37.3"},"publisher-location":"Cham","reference-count":16,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030219482"},{"type":"electronic","value":"9783030219499"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-21949-9_20","type":"book-chapter","created":{"date-parts":[[2019,5,29]],"date-time":"2019-05-29T09:27:07Z","timestamp":1559122027000},"page":"177-186","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["High-Resolution Ex Vivo Microstructural MRI After Restoring Ventricular Geometry via 3D Printing"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5759-5322","authenticated-orcid":false,"given":"Tyler E.","family":"Cork","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9010-2144","authenticated-orcid":false,"given":"Luigi E.","family":"Perotti","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7890-8559","authenticated-orcid":false,"given":"Ilya A.","family":"Verzhbinsky","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6533-1113","authenticated-orcid":false,"given":"Michael","family":"Loecher","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9051-3843","authenticated-orcid":false,"given":"Daniel B.","family":"Ennis","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,5,30]]},"reference":[{"issue":"2","key":"20_CR1","doi-asserted-by":"publisher","first-page":"717","DOI":"10.1002\/mrm.26166","volume":"77","author":"E Aliotta","year":"2017","unstructured":"Aliotta, E., Wu, H.H., Ennis, D.B.: Convex optimized diffusion encoding (CODE) gradient waveforms for minimum echo time and bulk motion-compensated diffusion-weighted MRI. Magn. Reson. Med. 77(2), 717\u2013729 (2017)","journal-title":"Magn. Reson. Med."},{"issue":"10","key":"20_CR2","doi-asserted-by":"publisher","first-page":"2243","DOI":"10.1007\/s10439-012-0593-5","volume":"40","author":"JD Bayer","year":"2012","unstructured":"Bayer, J.D., Blake, R.C., Plank, G., Trayanova, N.A.: A novel rule-based algorithm for assigning myocardial fiber orientation to computational heart models. Ann. Biomed. Eng. 40(10), 2243\u20132254 (2012)","journal-title":"Ann. Biomed. Eng."},{"issue":"1","key":"20_CR3","doi-asserted-by":"publisher","first-page":"136","DOI":"10.1002\/mrm.20741","volume":"55","author":"DB Ennis","year":"2006","unstructured":"Ennis, D.B., Kindlmann, G.: Orthogonal tensor invariants and the analysis of diffusion tensor magnetic resonance images. Magn. Reson. Med. Off. J. Int. Soc. Magn. Reson. Med. 55(1), 136\u2013146 (2006)","journal-title":"Magn. Reson. Med. Off. J. Int. Soc. Magn. Reson. Med."},{"issue":"2","key":"20_CR4","doi-asserted-by":"publisher","first-page":"372","DOI":"10.1002\/mrm.10051","volume":"47","author":"P Kellman","year":"2002","unstructured":"Kellman, P., Arai, A.E., McVeigh, E.R., Aletras, A.H.: Phase-sensitive inversion recovery for detecting myocardial infarction using gadolinium-delayed hyperenhancement. Magn. Reson. Med. Off. J. Int. Soc. Magn. Reson. Med. 47(2), 372\u2013383 (2002)","journal-title":"Magn. Reson. Med. Off. J. Int. Soc. Magn. Reson. Med."},{"key":"20_CR5","doi-asserted-by":"crossref","unstructured":"Kung, G.L., et al.: Microstructural infarct border zone remodeling in the post-infarct swine heart measured by diffusion tensor MRI. Front. Physiol. 9 (2018)","DOI":"10.3389\/fphys.2018.00826"},{"issue":"6","key":"20_CR6","doi-asserted-by":"publisher","first-page":"661","DOI":"10.1016\/j.jacc.2016.11.051","volume":"69","author":"S Nielles-Vallespin","year":"2017","unstructured":"Nielles-Vallespin, S., et al.: Assessment of myocardial microstructural dynamics by in vivo diffusion tensor cardiac magnetic resonance. J. Am. Coll. Cardiol. 69(6), 661\u2013676 (2017)","journal-title":"J. Am. Coll. Cardiol."},{"issue":"6","key":"20_CR7","doi-asserted-by":"publisher","first-page":"e1004968","DOI":"10.1371\/journal.pcbi.1004968","volume":"12","author":"AV Ponnaluri","year":"2016","unstructured":"Ponnaluri, A.V., et al.: Electrophysiology of heart failure using a rabbit model: from the failing myocyte to ventricular fibrillation. PLoS Comput. Biol. 12(6), e1004968 (2016)","journal-title":"PLoS Comput. Biol."},{"key":"20_CR8","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1016\/j.jmbbm.2018.07.005","volume":"87","author":"K Sack","year":"2018","unstructured":"Sack, K., et al.: Effect of intra-myocardial Algisyl-LVR\n                      \n                        \n                      \n                      $$^{{{TM}}}$$\n                      \n                        \n                          \n                            \n                            \n                              TM\n                            \n                          \n                        \n                      \n                     injectates on fibre structure in porcine heart failure. J. Mech. Behav. Biomed. Mater. 87, 172\u2013179 (2018)","journal-title":"J. Mech. Behav. Biomed. Mater."},{"issue":"9","key":"20_CR9","doi-asserted-by":"publisher","first-page":"e107159","DOI":"10.1371\/journal.pone.0107159","volume":"9","author":"CT Stoeck","year":"2014","unstructured":"Stoeck, C.T., et al.: Dual-phase cardiac diffusion tensor imaging with strain correction. PLoS One 9(9), e107159 (2014)","journal-title":"PLoS One"},{"key":"20_CR10","doi-asserted-by":"publisher","first-page":"30573","DOI":"10.1038\/srep30573","volume":"6","author":"I Teh","year":"2016","unstructured":"Teh, I., et al.: Resolving fine cardiac structures in rats with high-resolution diffusion tensor imaging. Sci. Rep. 6, 30573 (2016)","journal-title":"Sci. Rep."},{"key":"20_CR11","doi-asserted-by":"crossref","unstructured":"Verzhbinsky, I.A., Magrath, P., Aliotta, E., Ennis, D.B., Perotti, L.E.: Time resolved displacement-based registration of in vivo cDTI cardiomyocyte orientations. In: 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), pp. 474\u2013478. IEEE (2018)","DOI":"10.1109\/ISBI.2018.8363619"},{"issue":"5","key":"20_CR12","doi-asserted-by":"publisher","first-page":"773","DOI":"10.1016\/j.media.2009.07.006","volume":"13","author":"VY Wang","year":"2009","unstructured":"Wang, V.Y., Lam, H., Ennis, D.B., Cowan, B.R., Young, A.A., Nash, M.P.: Modelling passive diastolic mechanics with quantitative MRI of cardiac structure and function. Med. Image Anal. 13(5), 773\u2013784 (2009)","journal-title":"Med. Image Anal."},{"issue":"5","key":"20_CR13","first-page":"601","volume":"30","author":"HF Wehrl","year":"2015","unstructured":"Wehrl, H.F., et al.: Assessment of murine brain tissue shrinkage caused by different histological fixatives using magnetic resonance and computed tomography imaging. Histol. Histopathol. 30(5), 601\u2013613 (2015)","journal-title":"Histol. Histopathol."},{"issue":"6","key":"20_CR14","doi-asserted-by":"publisher","first-page":"594","DOI":"10.1016\/j.media.2005.04.005","volume":"9","author":"I Wolf","year":"2005","unstructured":"Wolf, I., et al.: The medical imaging interaction toolkit. Med. Image Anal. 9(6), 594\u2013604 (2005)","journal-title":"Med. Image Anal."},{"issue":"1","key":"20_CR15","doi-asserted-by":"publisher","first-page":"270","DOI":"10.1002\/jmri.26189","volume":"49","author":"HH Wu","year":"2019","unstructured":"Wu, H.H., et al.: A system using patient-specific 3D-printed molds to spatially align in vivo MRI with ex vivo MRI and whole-mount histopathology for prostate cancer research. J. Magn. Reson. Imaging 49(1), 270\u2013279 (2019)","journal-title":"J. Magn. Reson. Imaging"},{"issue":"4","key":"20_CR16","doi-asserted-by":"publisher","first-page":"1089","DOI":"10.1002\/mrm.22503","volume":"64","author":"X Zhong","year":"2010","unstructured":"Zhong, X., Spottiswoode, B.S., Meyer, C.H., Kramer, C.M., Epstein, F.H.: Imaging three-dimensional myocardial mechanics using navigator-gated volumetric spiral cine DENSE MRI. Magn. Reson. Med. 64(4), 1089\u20131097 (2010)","journal-title":"Magn. Reson. Med."}],"container-title":["Lecture Notes in Computer Science","Functional Imaging and Modeling of the Heart"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-21949-9_20","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,29]],"date-time":"2019-05-29T09:30:41Z","timestamp":1559122241000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-21949-9_20"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030219482","9783030219499"],"references-count":16,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-21949-9_20","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"30 May 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"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":"Bordeaux","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"France","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 June 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 June 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"fimh2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/fimh2019.sciencesconf.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"OCS","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"50","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"46","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"92% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"2,1","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"2","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}}]}}