{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T19:29:57Z","timestamp":1743017397641,"version":"3.40.3"},"publisher-location":"Cham","reference-count":13,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030326944"},{"type":"electronic","value":"9783030326951"}],"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\/978-3-030-32695-1_12","type":"book-chapter","created":{"date-parts":[[2019,10,10]],"date-time":"2019-10-10T17:10:36Z","timestamp":1570727436000},"page":"103-111","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Automated Quantification of Enlarged Perivascular Spaces in Clinical Brain MRI Across Sites"],"prefix":"10.1007","author":[{"given":"Florian","family":"Dubost","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Max","family":"D\u00fcnnwald","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Denver","family":"Huff","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vincent","family":"Scheumann","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Frank","family":"Schreiber","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Meike","family":"Vernooij","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wiro","family":"Niessen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Martin","family":"Skalej","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stefanie","family":"Schreiber","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Steffen","family":"Oeltze-Jafra","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marleen","family":"de Bruijne","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,10,7]]},"reference":[{"issue":"6","key":"12_CR1","doi-asserted-by":"publisher","first-page":"1732","DOI":"10.1161\/STROKEAHA.111.000620","volume":"44","author":"HH Adams","year":"2013","unstructured":"Adams, H.H., et al.: Rating method for dilated Virchow-Robin spaces on magnetic resonance imaging. Stroke 44(6), 1732\u20131735 (2013)","journal-title":"Stroke"},{"issue":"2","key":"12_CR2","doi-asserted-by":"publisher","first-page":"632","DOI":"10.1148\/radiol.2017170205","volume":"286","author":"EL Boespflug","year":"2017","unstructured":"Boespflug, E.L., et al.: MR imaging-based multimodal autoidentification of perivascular spaces (mMAPS): automated morphologic segmentation of enlarged perivascular spaces at clinical field strength. Radiology 286(2), 632\u2013642 (2017)","journal-title":"Radiology"},{"issue":"12","key":"12_CR3","doi-asserted-by":"publisher","first-page":"1157","DOI":"10.1212\/WNL.0000000000003746","volume":"88","author":"A Charidimou","year":"2017","unstructured":"Charidimou, A., et al.: MRI-visible perivascular spaces in cerebral amyloid angiopathy and hypertensive arteriopathy. Neurology 88(12), 1157\u20131164 (2017)","journal-title":"Neurology"},{"key":"12_CR4","doi-asserted-by":"publisher","first-page":"534","DOI":"10.1016\/j.neuroimage.2018.10.026","volume":"185","author":"F Dubost","year":"2019","unstructured":"Dubost, F., et al.: Enlarged perivascular spaces in brain MRI: automated quantification in four regions. NeuroImage 185, 534\u2013544 (2019)","journal-title":"NeuroImage"},{"key":"12_CR5","doi-asserted-by":"crossref","unstructured":"Dubost, F., et al.: Weakly Supervised Object Detection with 2D and 3D Regression Neural Networks. arXiv preprint arXiv:1906.01891 (2019)","DOI":"10.1016\/j.media.2020.101767"},{"key":"12_CR6","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1016\/j.media.2018.10.008","volume":"51","author":"F Dubost","year":"2019","unstructured":"Dubost, F., et al.: 3D regression neural network for the quantification of enlarged perivascular spaces in brain MRI. Med. Image Anal. 51, 89\u2013100 (2019)","journal-title":"Med. Image Anal."},{"issue":"9","key":"12_CR7","doi-asserted-by":"publisher","first-page":"807","DOI":"10.1007\/s10654-017-0321-4","volume":"32","author":"MA Ikram","year":"2017","unstructured":"Ikram, M.A., et al.: The Rotterdam Study: 2018 update on objectives, design and main results. Eur. J. Epidemiol. 32(9), 807\u2013850 (2017)","journal-title":"Eur. J. Epidemiol."},{"issue":"3\u20134","key":"12_CR8","doi-asserted-by":"publisher","first-page":"224","DOI":"10.1159\/000375153","volume":"39","author":"GM Potter","year":"2015","unstructured":"Potter, G.M., et al.: Cerebral perivascular spaces visible on magnetic resonance imaging: development of a qualitative rating scale and its observer reliability. Cerebrovasc. Dis. 39(3\u20134), 224\u2013231 (2015)","journal-title":"Cerebrovasc. Dis."},{"key":"12_CR9","doi-asserted-by":"publisher","first-page":"S208","DOI":"10.1016\/j.neuroimage.2004.07.051","volume":"23","author":"SM Smith","year":"2004","unstructured":"Smith, S.M., et al.: Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage 23, S208\u2013S219 (2004)","journal-title":"Neuroimage"},{"key":"12_CR10","unstructured":"Sudre, C.H., et al.: 3D multirater RCNN for multimodal multiclass detection and characterisation of extremely small objects. In: MIDL 2019 (2018)"},{"key":"12_CR11","doi-asserted-by":"crossref","unstructured":"van Wijnen, K.M., et al.: Automated lesion detection by regressing intensity-based distance with a neural network. In: MICCAI (2019)","DOI":"10.1007\/978-3-030-32251-9_26"},{"issue":"6","key":"12_CR12","doi-asserted-by":"publisher","first-page":"539","DOI":"10.1016\/S1474-4422(18)30145-5","volume":"17","author":"D Wilson","year":"2018","unstructured":"Wilson, D., et al.: Cerebral microbleeds and intracranial haemorrhage risk in patients anticoagulated for atrial fibrillation after acute ischaemic stroke or transient ischaemic attack (CROMIS-2): a multicentre observational cohort study. Lancet Neurol. 17(6), 539\u2013547 (2018)","journal-title":"Lancet Neurol."},{"key":"12_CR13","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1007\/978-3-319-47157-0_8","volume-title":"Machine Learning in Medical Imaging","author":"J Zhang","year":"2016","unstructured":"Zhang, J., Gao, Y., Park, S.H., Zong, X., Lin, W., Shen, D.: Segmentation of perivascular spaces using vascular features and structured random forest from 7T MR image. In: Wang, L., Adeli, E., Wang, Q., Shi, Y., Suk, H.-I. (eds.) MLMI 2016. LNCS, vol. 10019, pp. 61\u201368. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-47157-0_8"}],"container-title":["Lecture Notes in Computer Science","OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical Neuroimaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-32695-1_12","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,10]],"date-time":"2024-10-10T00:12:21Z","timestamp":1728519141000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-32695-1_12"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030326944","9783030326951"],"references-count":13,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-32695-1_12","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":"7 October 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MLCN","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Machine Learning in Clinical Neuroimaging","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":"2","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"mlcn2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/mlcnws.com","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":"7","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":"6","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":"86% - 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":"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"}]}}