{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T21:00:38Z","timestamp":1762376438045,"version":"3.40.3"},"publisher-location":"Cham","reference-count":16,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030009182"},{"type":"electronic","value":"9783030009199"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"vor","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":[[2018]]},"DOI":"10.1007\/978-3-030-00919-9_24","type":"book-chapter","created":{"date-parts":[[2018,9,16]],"date-time":"2018-09-16T04:24:52Z","timestamp":1537071892000},"page":"205-213","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Reproducible White Matter Tract Segmentation Using 3D U-Net on a Large-scale DTI Dataset"],"prefix":"10.1007","author":[{"given":"Bo","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marius","family":"de Groot","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Meike W.","family":"Vernooij","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"M. Arfan","family":"Ikram","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wiro J.","family":"Niessen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Esther E.","family":"Bron","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,9,15]]},"reference":[{"issue":"4","key":"24_CR1","doi-asserted-by":"publisher","first-page":"632","DOI":"10.1212\/WNL.57.4.632","volume":"57","author":"M OSullivan","year":"2001","unstructured":"OSullivan, M., et al.: Evidence for cortical disconnection as a mechanism of age-related cognitive decline. Neurology 57(4), 632\u2013638 (2001)","journal-title":"Neurology"},{"issue":"3","key":"24_CR2","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1016\/j.jalz.2014.06.011","volume":"11","author":"M de Groot","year":"2015","unstructured":"de Groot, M., et al.: Tract-specific white matter degeneration in aging: the Rotterdam study. Alzheimer\u2019s Dement 11(3), 321\u2013330 (2015)","journal-title":"Alzheimer\u2019s Dement"},{"issue":"1","key":"24_CR3","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1016\/j.neuroimage.2007.06.041","volume":"39","author":"INC Lawes","year":"2008","unstructured":"Lawes, I.N.C., et al.: Atlas-based segmentation of white matter tracts of the human brain using diffusion tensor tractography and comparison with classical dissection. Neuroimage 39(1), 62\u201379 (2008)","journal-title":"Neuroimage"},{"issue":"11","key":"24_CR4","doi-asserted-by":"publisher","first-page":"1562","DOI":"10.1109\/TMI.2007.906785","volume":"26","author":"LJ O\u2019Donnell","year":"2007","unstructured":"O\u2019Donnell, L.J., Westin, C.F.: Automatic tractography segmentation using a high-dimensional white matter atlas. IEEE Trans. Med. Imaging 26(11), 1562\u20131575 (2007)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"24_CR5","doi-asserted-by":"publisher","first-page":"277","DOI":"10.1016\/j.neuroimage.2015.12.003","volume":"127","author":"A Yendiki","year":"2016","unstructured":"Yendiki, A., Reuter, M., Wilkens, P., Rosas, H.D., Fischl, B.: Joint reconstruction of white-matter pathways from longitudinal diffusion MRI data with anatomical priors. Neuroimage 127, 277\u2013286 (2016)","journal-title":"Neuroimage"},{"key":"24_CR6","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1007\/978-3-319-24574-4_28","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015","author":"O Ronneberger","year":"2015","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-net: convolutional networks for biomedical image segmentation. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015. LNCS, vol. 9351, pp. 234\u2013241. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-24574-4_28"},{"key":"24_CR7","doi-asserted-by":"crossref","unstructured":"Milletari, F., et al.: V-net: Fully convolutional neural networks for volumetric medical image segmentation. In: 3D Vision (3DV), pp. 565\u2013571. IEEE (2016)","DOI":"10.1109\/3DV.2016.79"},{"key":"24_CR8","unstructured":"Wasserthal, J., et al.: Direct white matter bundle segmentation using stacked u-nets. arXiv preprint arXiv:1703.02036 (2017)"},{"issue":"8","key":"24_CR9","doi-asserted-by":"publisher","first-page":"661","DOI":"10.1007\/s10654-015-0082-x","volume":"30","author":"A Hofman","year":"2015","unstructured":"Hofman, A., et al.: The Rotterdam study: 2016 objectives and design update. Eur. J. Epidemiol. 30(8), 661\u2013708 (2015)","journal-title":"Eur. J. Epidemiol."},{"issue":"1","key":"24_CR10","doi-asserted-by":"publisher","first-page":"196","DOI":"10.1109\/TMI.2009.2035616","volume":"29","author":"S Klein","year":"2010","unstructured":"Klein, S., Staring, M., Murphy, K., Viergever, M.A., Pluim, J.P.: Elastix: a toolbox for intensity-based medical image registration. IEEE Trans. Med. Imaging 29(1), 196\u2013205 (2010)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"24_CR11","first-page":"35","volume":"209","author":"A Leemans","year":"2009","unstructured":"Leemans, A., et al.: Exploredti: a graphical toolbox for processing, analyzing, and visualizing diffusion MR data. Int. Soc. Mag. Reson. Med. 209, 35\u201337 (2009)","journal-title":"Int. Soc. Mag. Reson. Med."},{"issue":"2","key":"24_CR12","doi-asserted-by":"publisher","first-page":"825","DOI":"10.1006\/nimg.2002.1132","volume":"17","author":"M Jenkinson","year":"2002","unstructured":"Jenkinson, M., et al.: Improved optimization for the robust and accurate linear registration and motion correction of brain images. Neuroimage 17(2), 825\u2013841 (2002)","journal-title":"Neuroimage"},{"key":"24_CR13","unstructured":"Dozat, T.: Incorporating nesterov momentum into adam (2016)"},{"issue":"1","key":"24_CR14","first-page":"43","volume":"8","author":"SS Choi","year":"2010","unstructured":"Choi, S.S., Cha, S.H., Tappert, C.C.: A survey of binary similarity and distance measures. J. Syst. Cybern. Inf. 8(1), 43\u201348 (2010)","journal-title":"J. Syst. Cybern. Inf."},{"key":"24_CR15","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)"},{"key":"24_CR16","doi-asserted-by":"crossref","unstructured":"Landis, J.R., Koch, G.G.: The measurement of observer agreement for categorical data. Biometrics pp. 159\u2013174 (1977)","DOI":"10.2307\/2529310"}],"container-title":["Lecture Notes in Computer Science","Machine Learning in Medical Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-00919-9_24","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,13]],"date-time":"2024-03-13T13:32:12Z","timestamp":1710336732000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-00919-9_24"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030009182","9783030009199"],"references-count":16,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-00919-9_24","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"15 September 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MLMI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Machine Learning in Medical Imaging","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Granada","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 September 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 September 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"mlmi-med2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/mlmi2018.web.unc.edu\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}