{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,3]],"date-time":"2025-08-03T04:17:24Z","timestamp":1754194644714,"version":"3.40.3"},"publisher-location":"Cham","reference-count":27,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030332259"},{"type":"electronic","value":"9783030332266"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"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":[[2019]]},"DOI":"10.1007\/978-3-030-33226-6_23","type":"book-chapter","created":{"date-parts":[[2019,10,30]],"date-time":"2019-10-30T15:24:59Z","timestamp":1572449099000},"page":"219-228","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["An As-Invariant-As-Possible $$\\text {GL}^+(3){}$$-Based Statistical Shape Model"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9415-0859","authenticated-orcid":false,"given":"Felix","family":"Ambellan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7964-3049","authenticated-orcid":false,"given":"Stefan","family":"Zachow","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1447-4069","authenticated-orcid":false,"given":"Christoph","family":"von Tycowicz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,10,10]]},"reference":[{"key":"23_CR1","series-title":"Advances in Experimental Medicine and Biology","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1007\/978-3-030-19385-0_5","volume-title":"Biomedical Visualisation","author":"F Ambellan","year":"2019","unstructured":"Ambellan, F., Lamecker, H., von Tycowicz, C., Zachow, S.: Statistical shape models: understanding and mastering variation in anatomy. In: Rea, P.M. (ed.) Biomedical Visualisation. AEMB, vol. 1156, 1st edn, pp. 67\u201384. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-19385-0_5","edition":"1"},{"key":"23_CR2","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1016\/j.media.2018.11.009","volume":"52","author":"F Ambellan","year":"2019","unstructured":"Ambellan, F., Tack, A., Ehlke, M., Zachow, S.: Automated segmentation of knee bone and cartilage combining statistical shape knowledge and convolutional neural networks. Med. Image Anal. 52, 109\u2013118 (2019)","journal-title":"Med. Image Anal."},{"doi-asserted-by":"crossref","unstructured":"Ambellan, F., Zachow, S., von Tycowicz, C.: A surface-theoretic approach for statistical shape modeling. In: Proceedings of Medical Image Computing and Computer Assisted Intervention (MICCAI) (2019, accepted for publication)","key":"23_CR3","DOI":"10.1007\/978-3-030-32251-9_3"},{"issue":"2","key":"23_CR4","doi-asserted-by":"publisher","first-page":"295","DOI":"10.1111\/cgf.12832","volume":"35","author":"C Brandt","year":"2016","unstructured":"Brandt, C., von Tycowicz, C., Hildebrandt, K.: Geometric flows of curves in shape space for processing motion of deformable objects. Comput. Graph Forum 35(2), 295\u2013305 (2016)","journal-title":"Comput. Graph Forum"},{"issue":"9","key":"23_CR5","doi-asserted-by":"publisher","first-page":"1780","DOI":"10.1016\/j.jbiomech.2010.02.015","volume":"43","author":"TL Bredbenner","year":"2010","unstructured":"Bredbenner, T.L., Eliason, T.D., Potter, R.S., Mason, R.L., Havill, L.M., Nicolella, D.P.: Statistical shape modeling describes variation in tibia and femur surface geometry between control and incidence groups from the osteoarthritis initiative database. J. Biomech. 43(9), 1780\u20131786 (2010)","journal-title":"J. Biomech."},{"issue":"8","key":"23_CR6","doi-asserted-by":"publisher","first-page":"1442","DOI":"10.1136\/annrheumdis-2013-204660","volume":"73","author":"PG Conaghan","year":"2014","unstructured":"Conaghan, P.G., Kloppenburg, M., Schett, G., Bijlsma, J.W., et al.: Osteoarthritis research priorities: a report from a eular ad hoc expert committee. Ann. Rheum. Dis. 73(8), 1442\u20131445 (2014)","journal-title":"Ann. Rheum. Dis."},{"issue":"1","key":"23_CR7","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1006\/cviu.1995.1004","volume":"61","author":"TF Cootes","year":"1995","unstructured":"Cootes, T.F., Taylor, C.J., Cooper, D.H., Graham, J.: Active shape models-their training and application. Comput. Vis. Image Underst. 61(1), 38\u201359 (1995)","journal-title":"Comput. Vis. Image Underst."},{"issue":"2","key":"23_CR8","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1007\/s11263-010-0367-1","volume":"90","author":"BC Davis","year":"2010","unstructured":"Davis, B.C., Fletcher, P.T., Bullitt, E., Joshi, S.: Population shape regression from random design data. Int. J. Comput. Vis. 90(2), 255\u2013266 (2010)","journal-title":"Int. J. Comput. Vis."},{"issue":"8","key":"23_CR9","doi-asserted-by":"publisher","first-page":"995","DOI":"10.1109\/TMI.2004.831793","volume":"23","author":"P Fletcher","year":"2004","unstructured":"Fletcher, P., Lu, C., Pizer, S., Joshi, S.: Principal geodesic analysis for the study of nonlinear statistics of shape. IEEE. Trans. Med. Imaging 23(8), 995\u20131005 (2004)","journal-title":"IEEE. Trans. Med. Imaging"},{"key":"23_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/978-3-642-33718-5_1","volume-title":"Computer Vision \u2013 ECCV 2012","author":"O Freifeld","year":"2012","unstructured":"Freifeld, O., Black, M.J.: Lie bodies: a manifold representation of 3D human shape. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012. LNCS, vol. 7572, pp. 1\u201314. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-33718-5_1"},{"unstructured":"Gallier, J.: Logarithms and square roots of real matrices existence, uniqueness and applications in medical imaging. arXiv preprint arXiv:0805.0245 (2018)","key":"23_CR11"},{"issue":"5","key":"23_CR12","doi-asserted-by":"publisher","first-page":"158","DOI":"10.1145\/2908736","volume":"35","author":"L Gao","year":"2016","unstructured":"Gao, L., Lai, Y.K., Liang, D., Chen, S.Y., Xia, S.: Efficient and flexible deformation representation for data-driven surface modeling. ACM Trans. Graph 35(5), 158 (2016)","journal-title":"ACM Trans. Graph"},{"issue":"2","key":"23_CR13","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1111\/j.1467-8659.2009.01373.x","volume":"28","author":"N Hasler","year":"2009","unstructured":"Hasler, N., Stoll, C., Sunkel, M., Rosenhahn, B., Seidel, H.P.: A statistical model of human pose and body shape. Comput. Graph Forum 28(2), 337\u2013346 (2009)","journal-title":"Comput. Graph Forum"},{"issue":"5","key":"23_CR14","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1111\/cgf.13500","volume":"37","author":"B Heeren","year":"2018","unstructured":"Heeren, B., Zhang, C., Rumpf, M., Smith, W.: Principal geodesic analysis in the space of discrete shells. Comput. Graph Forum 37(5), 173\u2013184 (2018)","journal-title":"Comput. Graph Forum"},{"issue":"4","key":"23_CR15","doi-asserted-by":"publisher","first-page":"1179","DOI":"10.1137\/04061101X","volume":"26","author":"NJ Higham","year":"2005","unstructured":"Higham, N.J.: The scaling and squaring method for the matrix exponential revisited. SIAM J. Matrix Anal. Appl. 26(4), 1179\u20131193 (2005)","journal-title":"SIAM J. Matrix Anal. Appl."},{"doi-asserted-by":"crossref","unstructured":"Kilian, M., Mitra, N.J., Pottmann, H.: Geometric modeling in shape space. ACM Trans. Graph. (SIGGRAPH) 26(3), #64, 1\u20138 (2007)","key":"23_CR16","DOI":"10.1145\/1276377.1276457"},{"issue":"1","key":"23_CR17","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1002\/art.23176","volume":"58","author":"RC Lawrence","year":"2008","unstructured":"Lawrence, R.C., et al.: Estimates of the prevalence of arthritis and other rheumatic conditions in the united states: part II. Arthritis Rheumatol. 58(1), 26\u201335 (2008)","journal-title":"Arthritis Rheumatol."},{"issue":"3","key":"23_CR18","doi-asserted-by":"publisher","first-page":"323","DOI":"10.3934\/jgm.2016010","volume":"8","author":"RJ Martin","year":"2016","unstructured":"Martin, R.J., Neff, P.: Minimal geodesics on GL(n) for left-invariant, right-O(n)-invariant Riemannian metrics. J. Geom. Mech. 8(3), 323\u2013357 (2016)","journal-title":"J. Geom. Mech."},{"key":"23_CR19","doi-asserted-by":"publisher","first-page":"447","DOI":"10.1146\/annurev-bioeng-071114-040601","volume":"17","author":"MI Miller","year":"2015","unstructured":"Miller, M.I., Trouv\u00e9, A., Younes, L.: Hamiltonian systems and optimal control in computational anatomy: 100 years since d\u2019arcy thompson. Annu. Rev. Biomed. Eng. 17, 447\u2013509 (2015)","journal-title":"Annu. Rev. Biomed. Eng."},{"issue":"8","key":"23_CR20","doi-asserted-by":"publisher","first-page":"2048","DOI":"10.1002\/art.37987","volume":"65","author":"T Neogi","year":"2013","unstructured":"Neogi, T., et al.: Magnetic resonance imaging-based three-dimensional bone shape of the knee predicts onset of knee osteoarthritis. Arthritis Rheum. 65(8), 2048\u20132058 (2013)","journal-title":"Arthritis Rheum."},{"key":"23_CR21","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1007\/978-3-642-30232-9_7","volume-title":"Matrix Information Geometry","author":"X Pennec","year":"2013","unstructured":"Pennec, X., Arsigny, V.: Exponential barycenters of the canonical Cartan connection and invariant means on Lie groups. In: Nielsen, F., Bhatia, R. (eds.) Matrix Information Geometry, pp. 123\u2013166. Springer, Heidelberg (2013). https:\/\/doi.org\/10.1007\/978-3-642-30232-9_7"},{"key":"23_CR22","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1007\/978-3-319-24571-3_16","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015","author":"J Thomson","year":"2015","unstructured":"Thomson, J., O\u2019Neill, T., Felson, D., Cootes, T.: Automated shape and texture analysis for detection of osteoarthritis from radiographs of the knee. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015. LNCS, vol. 9350, pp. 127\u2013134. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-24571-3_16"},{"key":"23_CR23","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1007\/978-3-319-47157-0_6","volume-title":"Machine Learning in Medical Imaging","author":"J Thomson","year":"2016","unstructured":"Thomson, J., O\u2019Neill, T., Felson, D., Cootes, T.: Detecting osteophytes in radiographs of the knee to diagnose osteoarthritis. In: Wang, L., Adeli, E., Wang, Q., Shi, Y., Suk, H.-I. (eds.) MLMI 2016. LNCS, vol. 10019, pp. 45\u201352. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-47157-0_6"},{"key":"23_CR24","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.media.2017.09.004","volume":"43","author":"C von Tycowicz","year":"2018","unstructured":"von Tycowicz, C., Ambellan, F., Mukhopadhyay, A., Zachow, S.: An efficient Riemannian statistical shape model using differential coordinates. Med. Image Anal. 43, 1\u20139 (2018)","journal-title":"Med. Image Anal."},{"doi-asserted-by":"crossref","unstructured":"von Tycowicz, C., Schulz, C., Seidel, H.P., Hildebrandt, K.: Real-time nonlinear shape interpolation. ACM Trans. Graph 34(3), 34:1\u201334:10 (2015)","key":"23_CR25","DOI":"10.1145\/2729972"},{"issue":"3","key":"23_CR26","doi-asserted-by":"publisher","first-page":"769","DOI":"10.1016\/S1053-8119(03)00019-3","volume":"18","author":"RP Woods","year":"2003","unstructured":"Woods, R.P.: Characterizing volume and surface deformations in an atlas framework: theory, applications, and implementation. NeuroImage 18(3), 769\u2013788 (2003)","journal-title":"NeuroImage"},{"issue":"1\u20132","key":"23_CR27","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1007\/s10851-013-0479-7","volume":"50","author":"E Zacur","year":"2014","unstructured":"Zacur, E., Bossa, M., Olmos, S.: Multivariate tensor-based morphometry with a right-invariant riemannian distance on GL+(n). J. Math. Imaging Vis. 50(1\u20132), 18\u201331 (2014)","journal-title":"J. Math. Imaging Vis."}],"container-title":["Lecture Notes in Computer Science","Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-33226-6_23","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,10]],"date-time":"2024-10-10T00:16:30Z","timestamp":1728519390000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-33226-6_23"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030332259","9783030332266"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-33226-6_23","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":"10 October 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MFCA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Mathematical Foundations of Computational Anatomy","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shenzhen","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","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":"17 October 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 October 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"mfca2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/sites.google.com\/site\/mfca2019\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"8","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"7","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"88% - 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 (provided by the conference organizers)"}},{"value":"2","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"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 (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}