{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T00:59:55Z","timestamp":1776819595706,"version":"3.51.2"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030322472","type":"print"},{"value":"9783030322489","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\/978-3-030-32248-9_2","type":"book-chapter","created":{"date-parts":[[2019,10,9]],"date-time":"2019-10-09T23:08:49Z","timestamp":1570662529000},"page":"12-20","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["A Two-Stage Multi-loss Super-Resolution Network for Arterial Spin Labeling Magnetic Resonance Imaging"],"prefix":"10.1007","author":[{"given":"Zheng","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingping","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yiran","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiu","family":"Ge","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuanqi","family":"Shang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Donghui","family":"Song","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ze","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Shi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,10,10]]},"reference":[{"issue":"1","key":"2_CR1","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1002\/mrm.1910230106","volume":"23","author":"JA Detre","year":"1992","unstructured":"Detre, J.A., Leigh, J.S., Williams, D.S., et al.: Perfusion imaging. Magn. Reson. Med. 23(1), 37\u201345 (1992)","journal-title":"Magn. Reson. Med."},{"issue":"1","key":"2_CR2","doi-asserted-by":"publisher","first-page":"102","DOI":"10.1002\/mrm.25197","volume":"73","author":"DC Alsop","year":"2015","unstructured":"Alsop, D.C., Detre, J.A., Golay, X., et al.: Recommended implementation of arterial spin-labeled perfusion MRI for clinical applications: a consensus of the ISMRM perfusion study group and the European consortium for ASL in dementia. Magn. Reson. Med. 73(1), 102\u2013116 (2015)","journal-title":"Magn. Reson. Med."},{"issue":"7","key":"2_CR3","doi-asserted-by":"publisher","first-page":"1215","DOI":"10.1212\/01.wnl.0000238163.71349.78","volume":"67","author":"AT Du","year":"2006","unstructured":"Du, A.T., Jahng, G.H., Hayasaka, S., et al.: Hypoperfusion in frontotemporal dementia and Alzheimer disease by arterial spin labeling MRI. Neurology 67(7), 1215\u20131220 (2006)","journal-title":"Neurology"},{"key":"2_CR4","doi-asserted-by":"crossref","unstructured":"Asllani, I., Borogovac, A., Brown, T.R.: Regression algorithm correcting for partial volume effects in arterial spin labeling MRI. Magn. Reson. Med. Off. J. Int. Soc. Magn. Reson. Med. 60(6), 1362\u20131371 (2008)","DOI":"10.1002\/mrm.21670"},{"key":"2_CR5","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1016\/j.neuroimage.2019.01.004","volume":"189","author":"C Meur\u00e9e","year":"2019","unstructured":"Meur\u00e9e, C., Maurel, P., Ferr\u00e9, J.C., et al.: Patch-based super-resolution of arterial spin labeling magnetic resonance images. Neuroimage 189, 85\u201394 (2019)","journal-title":"Neuroimage"},{"key":"2_CR6","first-page":"246","volume-title":"MICCAI 2016","author":"O Oktay","year":"2016","unstructured":"Oktay, O., Bai, W., Lee, M., et al.: Multi-input cardiac image super-resolution using convolutional neural networks. In: Ourselin, S., Joskowicz, L., Sabuncu, M.R., Unal, G., Wells, W. (eds.) MICCAI 2016, vol. 9902, pp. 246\u2013254. Springer, Cham (2016)"},{"issue":"8","key":"2_CR7","doi-asserted-by":"publisher","first-page":"085011","DOI":"10.1088\/1361-6560\/aab9e9","volume":"63","author":"J Shi","year":"2018","unstructured":"Shi, J., Liu, Q., Wang, C., et al.: Super-resolution reconstruction of MR image with a novel residual learning network algorithm. Phys. Med. Biol. 63(8), 085011 (2018)","journal-title":"Phys. Med. Biol."},{"issue":"3","key":"2_CR8","doi-asserted-by":"publisher","first-page":"1129","DOI":"10.1109\/JBHI.2018.2843819","volume":"23","author":"J Shi","year":"2018","unstructured":"Shi, J., Li, Z., Ying, S., et al.: MR image super-resolution via wide residual networks with fixed skip connection. IEEE J. Biomed. Health Inform. 23(3), 1129\u20131140 (2018)","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"2_CR9","doi-asserted-by":"crossref","unstructured":"Tong, T., Li, G., Liu, X., et al.: Image super-resolution using dense skip connections. In: ICCV, pp. 4799\u20134807 (2017)","DOI":"10.1109\/ICCV.2017.514"},{"key":"2_CR10","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Tian, Y., Kong, Y., et al.: Residual dense network for image super-resolution. In: CVPR, pp. 2472\u20132481 (2018)","DOI":"10.1109\/CVPR.2018.00262"},{"key":"2_CR11","doi-asserted-by":"crossref","unstructured":"Huang, G., Liu, Z., Van Der Maaten, L., et al.: Densely connected convolutional networks. In: CVPR, pp. 4700\u20134708 (2017)","DOI":"10.1109\/CVPR.2017.243"},{"key":"2_CR12","unstructured":"Guo, Y., Chen, Q., Chen, J., et al. Dual reconstruction nets for image super-resolution with gradient sensitive loss. arXiv preprint arXiv:1809.07099 (2018)"},{"key":"2_CR13","doi-asserted-by":"crossref","unstructured":"Kim, J., Kwon Lee, J., Mu Lee, K.: Accurate image super-resolution using very deep convolutional networks. In: CVPR, pp. 1646\u20131654 (2016)","DOI":"10.1109\/CVPR.2016.182"},{"key":"2_CR14","doi-asserted-by":"crossref","unstructured":"Tai, Y., Yang, J., Liu, X.: Image super-resolution via deep recursive residual network. In: CVPR, pp. 3147\u20133155 (2017)","DOI":"10.1109\/CVPR.2017.298"},{"key":"2_CR15","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"286","DOI":"10.1007\/978-3-030-01234-2_18","volume-title":"ECCV 2018","author":"Y Zhang","year":"2018","unstructured":"Zhang, Y., Li, K., Li, K., et al.: Image super-resolution using very deep residual channel attention networks. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11211, pp. 286\u2013301. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01234-2_18"},{"issue":"7","key":"2_CR16","doi-asserted-by":"publisher","first-page":"3142","DOI":"10.1109\/TIP.2017.2662206","volume":"26","author":"K Zhang","year":"2017","unstructured":"Zhang, K., Zuo, W., Chen, Y., et al.: Beyond a gaussian denoiser: Residual learning of deep CNN for image denoising. IEEE Trans. Image Process. 26(7), 3142\u20133155 (2017)","journal-title":"IEEE Trans. Image Process."},{"issue":"12","key":"2_CR17","doi-asserted-by":"publisher","first-page":"2524","DOI":"10.1109\/TMI.2017.2715284","volume":"36","author":"H Chen","year":"2017","unstructured":"Chen, H., Zhang, Y., Kalra, M.K., et al.: Low-dose CT with a residual encoder-decoder convolutional neural network. IEEE Trans. Med. Imaging 36(12), 2524\u20132535 (2017)","journal-title":"IEEE Trans. Med. Imaging"}],"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\/978-3-030-32248-9_2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,10]],"date-time":"2024-10-10T00:21:13Z","timestamp":1728519673000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-32248-9_2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030322472","9783030322489"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-32248-9_2","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"}]}}