{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T18:42:39Z","timestamp":1760985759881,"version":"3.40.3"},"publisher-location":"Cham","reference-count":13,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030009304"},{"type":"electronic","value":"9783030009311"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"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":[[2018]]},"DOI":"10.1007\/978-3-030-00931-1_80","type":"book-chapter","created":{"date-parts":[[2018,9,12]],"date-time":"2018-09-12T23:26:09Z","timestamp":1536794769000},"page":"698-705","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Spatially Localized Atlas Network Tiles Enables 3D Whole Brain Segmentation from Limited Data"],"prefix":"10.1007","author":[{"given":"Yuankai","family":"Huo","sequence":"first","affiliation":[]},{"given":"Zhoubing","family":"Xu","sequence":"additional","affiliation":[]},{"given":"Katherine","family":"Aboud","sequence":"additional","affiliation":[]},{"given":"Prasanna","family":"Parvathaneni","sequence":"additional","affiliation":[]},{"given":"Shunxing","family":"Bao","sequence":"additional","affiliation":[]},{"given":"Camilo","family":"Bermudez","sequence":"additional","affiliation":[]},{"given":"Susan M.","family":"Resnick","sequence":"additional","affiliation":[]},{"given":"Laurie E.","family":"Cutting","sequence":"additional","affiliation":[]},{"given":"Bennett A.","family":"Landman","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,9,13]]},"reference":[{"issue":"7","key":"80_CR1","doi-asserted-by":"publisher","first-page":"1070","DOI":"10.1016\/j.media.2014.06.005","volume":"18","author":"AJ Asman","year":"2014","unstructured":"Asman, A.J., Landman, B.A.: Hierarchical performance estimation in the statistical label fusion framework. Med. Image Anal. 18(7), 1070\u20131081 (2014)","journal-title":"Med. Image Anal."},{"doi-asserted-by":"crossref","unstructured":"de Br\u00e9bisson, A., Montana, G.: Deep neural networks for anatomical brain segmentation. arXiv preprint arXiv:1502.02445 (2015)","key":"80_CR2","DOI":"10.1109\/CVPRW.2015.7301312"},{"key":"80_CR3","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"424","DOI":"10.1007\/978-3-319-46723-8_49","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2016","author":"\u00d6 \u00c7i\u00e7ek","year":"2016","unstructured":"\u00c7i\u00e7ek, \u00d6., Abdulkadir, A., Lienkamp, S.S., Brox, T., Ronneberger, O.: 3D U-net: learning dense volumetric segmentation from sparse annotation. In: Ourselin, S., Joskowicz, L., Sabuncu, M.R., Unal, G., Wells, W. (eds.) MICCAI 2016. LNCS, vol. 9901, pp. 424\u2013432. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46723-8_49"},{"issue":"3","key":"80_CR4","doi-asserted-by":"publisher","first-page":"463","DOI":"10.1109\/42.712135","volume":"17","author":"DL Collins","year":"1998","unstructured":"Collins, D.L., et al.: Design and construction of a realistic digital brain phantom. Trans. Med. Imaging 17(3), 463\u2013468 (1998)","journal-title":"Trans. Med. Imaging"},{"key":"80_CR5","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1007\/978-3-319-46720-7_10","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2016","author":"Y Huo","year":"2016","unstructured":"Huo, Y., Aboud, K., Kang, H., Cutting, L.E., Landman, B.A.: Mapping lifetime brain volumetry with covariate-adjusted restricted cubic spline regression from cross-sectional multi-site MRI. In: Ourselin, S., Joskowicz, L., Sabuncu, M.R., Unal, G., Wells, W. (eds.) MICCAI 2016. LNCS, vol. 9900, pp. 81\u201388. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46720-7_10"},{"key":"80_CR6","doi-asserted-by":"publisher","first-page":"319","DOI":"10.1007\/s12021-011-9133-y","volume":"10","author":"DN Kennedy","year":"2012","unstructured":"Kennedy, D.N., Haselgrove, C., Hodge, S.M., Rane, P.S., Makris, N., Frazier, J.A.: Candishare: a resource for pediatric neuroimaging data. Neuroinformatics 10, 319\u2013322 (2012)","journal-title":"Neuroinformatics"},{"key":"80_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"348","DOI":"10.1007\/978-3-319-59050-9_28","volume-title":"Information Processing in Medical Imaging","author":"W Li","year":"2017","unstructured":"Li, W., Wang, G., Fidon, L., Ourselin, S., Cardoso, M.J., Vercauteren, T.: On the compactness, efficiency, and representation of 3D convolutional networks: brain parcellation as a pretext task. In: Niethammer, M., Styner, M., Aylward, S., Zhu, H., Oguz, I., Yap, P.-T., Shen, D. (eds.) IPMI 2017. LNCS, vol. 10265, pp. 348\u2013360. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-59050-9_28"},{"issue":"9","key":"80_CR8","doi-asserted-by":"publisher","first-page":"1498","DOI":"10.1162\/jocn.2007.19.9.1498","volume":"19","author":"DS Marcus","year":"2007","unstructured":"Marcus, D.S., Wang, T.H., Parker, J., Csernansky, J.G., Morris, J.C., Buckner, R.L.: Open access series of imaging studies (oasis): cross-sectional mri data in young, middle aged, nondemented, and demented older adults. J. Cogn. Neurosci. 19(9), 1498\u20131507 (2007)","journal-title":"J. Cogn. Neurosci."},{"issue":"2","key":"80_CR9","doi-asserted-by":"publisher","first-page":"024003","DOI":"10.1117\/1.JMI.4.2.024003","volume":"4","author":"R Mehta","year":"2017","unstructured":"Mehta, R., Majumdar, A., Sivaswamy, J.: Brainsegnet: a convolutional neural network architecture for automated segmentation of human brain structures. J. Med. Imaging 4(2), 024003 (2017)","journal-title":"J. Med. Imaging"},{"issue":"1\u20132","key":"80_CR10","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1016\/S0262-8856(00)00052-4","volume":"19","author":"S Ourselin","year":"2001","unstructured":"Ourselin, S., Roche, A., Subsol, G., Pennec, X., Ayache, N.: Reconstructing a 3D structure from serial histological sections. Image Vis. Comput. 19(1\u20132), 25\u201331 (2001)","journal-title":"Image Vis. Comput."},{"key":"80_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"231","DOI":"10.1007\/978-3-319-66179-7_27","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2017","author":"AG Roy","year":"2017","unstructured":"Roy, A.G., Conjeti, S., Sheet, D., Katouzian, A., Navab, N., Wachinger, C.: Error corrective boosting for learning fully convolutional networks with limited data. In: Descoteaux, M., Maier-Hein, L., Franz, A., Jannin, P., Collins, D.L., Duchesne, S. (eds.) MICCAI 2017. LNCS, vol. 10435, pp. 231\u2013239. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-66179-7_27"},{"key":"80_CR12","doi-asserted-by":"publisher","first-page":"434","DOI":"10.1016\/j.neuroimage.2017.02.035","volume":"170","author":"C Wachinger","year":"2017","unstructured":"Wachinger, C., Reuter, M., Klein, T.: Deepnat: deep convolutional neural network for segmenting neuroanatomy. NeuroImage 170, 434\u2013445 (2017)","journal-title":"NeuroImage"},{"key":"80_CR13","first-page":"27","volume":"7","author":"H Wang","year":"2013","unstructured":"Wang, H., Yushkevich, P.: Multi-atlas segmentation with joint label fusion and corrective learning-an open source implementation. Front. Neuroinformatics 7, 27 (2013)","journal-title":"Front. Neuroinformatics"}],"container-title":["Lecture Notes in Computer Science","Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2018"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-00931-1_80","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,13]],"date-time":"2024-03-13T20:08:31Z","timestamp":1710360511000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-00931-1_80"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030009304","9783030009311"],"references-count":13,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-00931-1_80","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":"13 September 2018","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":"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":"20 September 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"miccai2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.miccai2018.org\/en\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}