{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T05:17:59Z","timestamp":1778822279838,"version":"3.51.4"},"publisher-location":"Cham","reference-count":12,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030322533","type":"print"},{"value":"9783030322540","type":"electronic"}],"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\/978-3-030-32254-0_72","type":"book-chapter","created":{"date-parts":[[2019,10,9]],"date-time":"2019-10-09T23:08:49Z","timestamp":1570662529000},"page":"646-654","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Discriminative Correlation Filter Network for Robust Landmark Tracking in Ultrasound Guided Intervention"],"prefix":"10.1007","author":[{"given":"Chunxu","family":"Shen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jishuai","family":"He","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yibin","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jian","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,10,10]]},"reference":[{"issue":"1","key":"72_CR1","doi-asserted-by":"publisher","first-page":"011715","DOI":"10.1118\/1.4855956","volume":"41","author":"C Riley","year":"2014","unstructured":"Riley, C., et al.: Dosimetric evaluation of the interplay effect in respiratory-gated RapidArc radiation therapy. Med. Phys. 41(1), 011715 (2014)","journal-title":"Med. Phys."},{"key":"72_CR2","unstructured":"Nouri, D., Rothberg, A.: Liver ultrasound tracking using a learned distance metric. In: MICCAI 2015 Challenge on Liver Ultrasound Tracking, Munich, Germany (2015)"},{"key":"72_CR3","doi-asserted-by":"crossref","unstructured":"Gomariz, A., et al.: Siamese networks with location prior for landmark tracking in liver ultrasound sequences. arXiv preprint arXiv:1901.08109 (2019)","DOI":"10.1109\/ISBI.2019.8759382"},{"key":"72_CR4","unstructured":"Hallack, A., et al.: Robust liver ultrasound tracking using dense distinctive image features. In: MICCAI 2015 Challenge on Liver Ultrasound Tracking, Munich, Germany (2015)"},{"issue":"11","key":"72_CR5","doi-asserted-by":"publisher","first-page":"5889","DOI":"10.1002\/mp.12574","volume":"44","author":"A Shepard","year":"2017","unstructured":"Shepard, A., et al.: A block matching based approach with multiple simultaneous templates for the real-time 2D ultrasound tracking of liver vessels. Med. Phys. 44(11), 5889\u20135900 (2017)","journal-title":"Med. Phys."},{"key":"72_CR6","unstructured":"Makhinya, M., Goksel, O.: Motion tracking in 2D ultrasound using vessel models and robust optic-flow. In: MICCAI 2015 Challenge on Liver Ultrasound Tracking, Munich, Germany (2015)"},{"issue":"10","key":"72_CR7","doi-asserted-by":"publisher","first-page":"1605","DOI":"10.1007\/s11548-018-1780-0","volume":"13","author":"T Williamson","year":"2018","unstructured":"Williamson, T., et al.: Ultrasound-based liver tracking utilizing a hybrid template\/optical flow approach. Int. J. Comput. Assist. Radiol. Surg. 13(10), 1605\u20131615 (2018)","journal-title":"Int. J. Comput. Assist. Radiol. Surg."},{"key":"72_CR8","unstructured":"Kondo, S.: Liver ultrasound tracking using kernelized correlation filter with adaptive window size selection. In: MICCAI 2015 Challenge on Liver Ultrasound Tracking, Munich, Germany (2015)"},{"issue":"6","key":"72_CR9","doi-asserted-by":"publisher","first-page":"941","DOI":"10.1007\/s11548-017-1559-8","volume":"12","author":"E Ozkan","year":"2017","unstructured":"Ozkan, E., et al.: Robust motion tracking in liver from 2D ultrasound images using supporters. Int. J. Comput. Assist. Radiol. Surg. 12(6), 941\u2013950 (2017)","journal-title":"Int. J. Comput. Assist. Radiol. Surg."},{"issue":"3","key":"72_CR10","doi-asserted-by":"publisher","first-page":"583","DOI":"10.1109\/TPAMI.2014.2345390","volume":"37","author":"J Henriques","year":"2015","unstructured":"Henriques, J., et al.: High-speed tracking with kernelized correlation filters. IEEE Trans. Pattern Anal. Mach. Intell. 37(3), 583\u2013596 (2015)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"14","key":"72_CR11","doi-asserted-by":"publisher","first-page":"5571","DOI":"10.1088\/0031-9155\/60\/14\/5571","volume":"60","author":"V Luca","year":"2015","unstructured":"Luca, V., et al.: The 2014 liver ultrasound tracking benchmark. Phys. Med. Biol. 60(14), 5571\u20135599 (2015)","journal-title":"Phys. Med. Biol."},{"key":"72_CR12","unstructured":"Christoph, B., et al.: On the computation of complex valued gradients with application to statistically optimum beamforming. arXiv preprint arXiv:1701.00392 (2019)"}],"container-title":["Lecture Notes in Computer Science","Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2019"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-32254-0_72","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,10]],"date-time":"2024-10-10T00:14:41Z","timestamp":1728519281000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-32254-0_72"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030322533","9783030322540"],"references-count":12,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-32254-0_72","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"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":"MICCAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Medical Image Computing and Computer-Assisted Intervention","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":"13 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":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"miccai2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.miccai2019.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 (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":"1730","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":"539","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":"31% - 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":"3.07","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":"6.31","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":"Yes","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"}]}}