{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,5]],"date-time":"2025-04-05T11:27:07Z","timestamp":1743852427827,"version":"3.40.3"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030317225"},{"type":"electronic","value":"9783030317232"}],"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\/978-3-030-31723-2_32","type":"book-chapter","created":{"date-parts":[[2019,10,31]],"date-time":"2019-10-31T00:05:31Z","timestamp":1572480331000},"page":"380-390","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Transfer Learning for Rigid 2D\/3D Cardiovascular Images Registration"],"prefix":"10.1007","author":[{"given":"Shaoya","family":"Guan","sequence":"first","affiliation":[]},{"given":"Cai","family":"Meng","sequence":"additional","affiliation":[]},{"given":"Kai","family":"Sun","sequence":"additional","affiliation":[]},{"given":"Tianmiao","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,10,31]]},"reference":[{"issue":"1","key":"32_CR1","doi-asserted-by":"publisher","first-page":"213","DOI":"10.1109\/TMI.2018.2859478","volume":"38","author":"VO Annegreet","year":"2019","unstructured":"Annegreet, V.O., Hakim, C.A., Vernooij, M.W., de Bruijne, M.: Convolutional neural networks for medical image analysis: full training or fine tuning? IEEE Trans. Med. Imaging 38(1), 213\u2013224 (2019)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"32_CR2","first-page":"1","volume":"54","author":"V Cheplygina","year":"2018","unstructured":"Cheplygina, V., de Bruijne, M., Pluim, J.P.W.: Not-so-supervised: a survey of semi-supervised, multi-instance, and transfer learning in medical image analysis. Med. Image Anal. 54, 1\u201324 (2018)","journal-title":"Med. Image Anal."},{"issue":"5","key":"32_CR3","doi-asserted-by":"publisher","first-page":"1486","DOI":"10.1109\/JBHI.2017.2769800","volume":"22","author":"V Cheplygina","year":"2018","unstructured":"Cheplygina, V., Pino, I., Pedersen, J., Lynch, D., S\u00f8rensen, L., de Bruijne, M.: Transfer learning for multicenter classification of chronic obstructive pulmonary disease. IEEE J. Biomed. Health Inform. 22(5), 1486\u20131496 (2018)","journal-title":"IEEE J. Biomed. Health Inform."},{"issue":"9","key":"32_CR4","doi-asserted-by":"publisher","first-page":"1095","DOI":"10.1016\/j.cviu.2013.02.009","volume":"117","author":"CR Chou","year":"2013","unstructured":"Chou, C.R., Frederick, B., Mageras, G., Chang, S., Pizer, S.: 2D\/3D image registration using regression learning. Comput. Vis. Image Underst. 117(9), 1095 (2013)","journal-title":"Comput. Vis. Image Underst."},{"key":"32_CR5","doi-asserted-by":"publisher","first-page":"17524","DOI":"10.1109\/ACCESS.2019.2894943","volume":"7","author":"S Guan","year":"2019","unstructured":"Guan, S., Meng, C., Xie, Y., Wang, Q., Sun, K., Wanga, T.: Deformable cardiovascular image registration via multi-channel convolutional neural network. IEEE Access 7, 17524\u201317534 (2019)","journal-title":"IEEE Access"},{"issue":"7","key":"32_CR6","doi-asserted-by":"publisher","first-page":"1527","DOI":"10.1162\/neco.2006.18.7.1527","volume":"18","author":"GE Hinton","year":"2006","unstructured":"Hinton, G.E., Osindero, S., Teh, Y.W.: A fast learning algorithm for deep belief nets. Neural Comput. 18(7), 1527\u20131554 (2006)","journal-title":"Neural Comput."},{"issue":"5","key":"32_CR7","doi-asserted-by":"publisher","first-page":"1285","DOI":"10.1109\/TMI.2016.2528162","volume":"35","author":"HC Shin","year":"2016","unstructured":"Shin, H.C., Roth, H.R., Gao, M., Lu, L., Xu, Z.: Deep convolutional neural networks for computer-aided detection: Cnn architectures, dataset characteristics and transfer learning. IEEE Trans. Med. Imaging 35(5), 1285\u20131298 (2016)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"32_CR8","doi-asserted-by":"crossref","unstructured":"Hu, Y., Modat, M., Gibson, E., et al.: Label-driven weakly-supervised learning for multimodal deformable image registration. In: IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), pp. 1070\u20131074. IEEE, Washington, DC (2018)","DOI":"10.1109\/ISBI.2018.8363756"},{"key":"32_CR9","doi-asserted-by":"crossref","unstructured":"Jia, Y., Shelhamer, E., Donahue, J., et al.: Caffe: convolutional architecture for fast feature embedding. In: Proceedings of the 22nd ACM International Conference on Multimedia, pp. 675\u2013678. ACM, Florida (2014)","DOI":"10.1145\/2647868.2654889"},{"issue":"11","key":"32_CR10","doi-asserted-by":"publisher","first-page":"4604","DOI":"10.1088\/1361-6560\/aa6b3e","volume":"62","author":"MD Ketcha","year":"2017","unstructured":"Ketcha, M.D., et al.: Multi-stage 3D\u20132D registration for correction of anatomical deformation in image-guided spine surgery. Phys. Med. Biol. 62(11), 4604 (2017)","journal-title":"Phys. Med. Biol."},{"issue":"9","key":"32_CR11","doi-asserted-by":"publisher","first-page":"1177","DOI":"10.1109\/TMI.2005.853240","volume":"24","author":"EBVD Kraats","year":"2005","unstructured":"Kraats, E.B.V.D., Penney, G.P., Tomazevic, D., Walsum, T.V., Niessen, W.J.: Standardized evaluation methodology for 2-D-3-D registration. IEEE Trans. Med. Imaging 24(9), 1177\u20131189 (2005)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"32_CR12","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, G.E.: ImageNet classification with deep convolutional neural networks. In: Advances in Neural Information Processing Systems, pp. 1097\u20131105. MIT Press, Lake Tahoe (2012)"},{"issue":"3","key":"32_CR13","doi-asserted-by":"publisher","first-page":"642","DOI":"10.1016\/j.media.2010.03.005","volume":"16","author":"P Markelj","year":"2012","unstructured":"Markelj, P., Tomazevic, D., Likar, B., Pernus, F.: A review of 3D\/2D registration methods for image-guided interventions. Med. Image Anal. 16(3), 642\u2013661 (2012)","journal-title":"Med. Image Anal."},{"issue":"5","key":"32_CR14","doi-asserted-by":"publisher","first-page":"1352","DOI":"10.1109\/TMI.2016.2521800","volume":"35","author":"S Miao","year":"2016","unstructured":"Miao, S., Wang, Z., Liao, R.: A CNN regression approach for real-time 2D\/3D registration. IEEE Trans. Med. Imaging 35(5), 1352\u20131363 (2016)","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"3","key":"32_CR15","first-page":"636","volume":"4","author":"S Miao","year":"2015","unstructured":"Miao, S., Wang, Z.J., Liao, R.: Real-time 2D\/3D registration via CNN regression. Optoelectron. Adv. Mater.-Rapid Commun. 4(3), 636\u2013648 (2015)","journal-title":"Optoelectron. Adv. Mater.-Rapid Commun."},{"issue":"5","key":"32_CR16","doi-asserted-by":"publisher","first-page":"1299","DOI":"10.1109\/TMI.2016.2535302","volume":"35","author":"T Nima","year":"2016","unstructured":"Nima, T., et al.: Convolutional neural networks for medical image analysis: full training or fine tuning? IEEE Trans. Med. Imaging 35(5), 1299\u20131312 (2016)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"32_CR17","doi-asserted-by":"publisher","first-page":"17809","DOI":"10.1109\/ACCESS.2019.2892455","volume":"7","author":"Z Swati","year":"2019","unstructured":"Swati, Z., et al.: Content-based brain tumor retrieval for MR images using transfer learning. IEEE Access 7, 17809\u201317822 (2019)","journal-title":"IEEE Access"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition and Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-31723-2_32","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,31]],"date-time":"2024-10-31T00:24:26Z","timestamp":1730334266000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-31723-2_32"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030317225","9783030317232"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-31723-2_32","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":"31 October 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PRCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chinese Conference on Pattern Recognition and Computer Vision  (PRCV)","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Xi'an","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":"8 November 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 November 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ccprcv2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.prcv2019.com\/en\/index.html","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 (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":"412","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":"165","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":"40% - 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":"4","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":"4","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)"}}]}}