{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T12:25:45Z","timestamp":1775737545618,"version":"3.50.1"},"publisher-location":"Cham","reference-count":19,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783319590493","type":"print"},{"value":"9783319590509","type":"electronic"}],"license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"unspecified","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":[[2017]]},"DOI":"10.1007\/978-3-319-59050-9_47","type":"book-chapter","created":{"date-parts":[[2017,5,22]],"date-time":"2017-05-22T12:36:11Z","timestamp":1495456571000},"page":"597-609","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":299,"title":["Unsupervised Domain Adaptation in Brain Lesion Segmentation with Adversarial Networks"],"prefix":"10.1007","author":[{"given":"Konstantinos","family":"Kamnitsas","sequence":"first","affiliation":[]},{"given":"Christian","family":"Baumgartner","sequence":"additional","affiliation":[]},{"given":"Christian","family":"Ledig","sequence":"additional","affiliation":[]},{"given":"Virginia","family":"Newcombe","sequence":"additional","affiliation":[]},{"given":"Joanna","family":"Simpson","sequence":"additional","affiliation":[]},{"given":"Andrew","family":"Kane","sequence":"additional","affiliation":[]},{"given":"David","family":"Menon","sequence":"additional","affiliation":[]},{"given":"Aditya","family":"Nori","sequence":"additional","affiliation":[]},{"given":"Antonio","family":"Criminisi","sequence":"additional","affiliation":[]},{"given":"Daniel","family":"Rueckert","sequence":"additional","affiliation":[]},{"given":"Ben","family":"Glocker","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,5,23]]},"reference":[{"issue":"1\u20132","key":"47_CR1","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1007\/s10994-009-5152-4","volume":"79","author":"S Ben-David","year":"2010","unstructured":"Ben-David, S., Blitzer, J., Crammer, K., Kulesza, A., Pereira, F., Vaughan, J.W.: A theory of learning from different domains. Mach. Learn. 79(1\u20132), 151\u2013175 (2010)","journal-title":"Mach. Learn."},{"key":"47_CR2","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"326","DOI":"10.1007\/978-3-319-46723-8_38","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2016","author":"R Berm\u00fadez-Chac\u00f3n","year":"2016","unstructured":"Berm\u00fadez-Chac\u00f3n, R., Becker, C., Salzmann, M., Fua, P.: Scalable unsupervised domain adaptation for electron microscopy. In: Ourselin, S., Joskowicz, L., Sabuncu, M.R., Unal, G., Wells, W. (eds.) MICCAI 2016. LNCS, vol. 9901, pp. 326\u2013334. Springer, Cham (2016). doi:10.1007\/978-3-319-46723-8_38"},{"issue":"1","key":"47_CR3","first-page":"195","volume":"26","author":"F Ciompi","year":"2015","unstructured":"Ciompi, F., de Hoop, B., van Riel, S.J., Chung, K., Scholten, E.T., Oudkerk, M., de Jong, P.A., Prokop, M., van Ginneken, B.: Automatic classification of pulmonary peri-fissural nodules in computed tomography using an ensemble of 2D views and a convolutional neural network out-of-the-box. MedIA 26(1), 195\u2013202 (2015)","journal-title":"MedIA"},{"issue":"59","key":"47_CR4","first-page":"1","volume":"17","author":"Y Ganin","year":"2016","unstructured":"Ganin, Y., Ustinova, E., Ajakan, H., Germain, P., Larochelle, H., Laviolette, F., Marchand, M., Lempitsky, V.: Domain-adversarial training of neural networks. J. Mach. Learn. Res. 17(59), 1\u201335 (2016)","journal-title":"J. Mach. Learn. Res."},{"key":"47_CR5","unstructured":"Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., Bengio, Y.: Generative adversarial nets. In: NIPS (2014)"},{"key":"47_CR6","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1007\/978-3-642-40760-4_7","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2013","author":"T Heimann","year":"2013","unstructured":"Heimann, T., Mountney, P., John, M., Ionasec, R.: Learning without labeling: domain adaptation for ultrasound transducer localization. In: Mori, K., Sakuma, I., Sato, Y., Barillot, C., Navab, N. (eds.) MICCAI 2013. LNCS, vol. 8151, pp. 49\u201356. Springer, Heidelberg (2013). doi:10.1007\/978-3-642-40760-4_7"},{"key":"47_CR7","unstructured":"Jiang, J.: A literature survey on domain adaptation of statistical classifiers (2008). http:\/\/sifaka.cs.uiuc.edu\/jiang4\/domain_adaptation\/survey\/da_survey.pdf"},{"key":"47_CR8","first-page":"61","volume":"36","author":"K Kamnitsas","year":"2016","unstructured":"Kamnitsas, K., Ledig, C., Newcombe, V.F., Simpson, J.P., Kane, A.D., Menon, D.K., Rueckert, D., Glocker, B.: Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation. MedIA 36, 61\u201378 (2016)","journal-title":"MedIA"},{"key":"47_CR9","unstructured":"Lee, C.Y., Xie, S., Gallagher, P., Zhang, Z., Tu, Z.: Deeply-supervised nets. In: AISTATS, vol. 2, p. 6 (2015)"},{"key":"47_CR10","doi-asserted-by":"crossref","unstructured":"Long, J., Shelhamer, E., Darrell, T.: Fully convolutional networks for semantic segmentation. In: CVPR (2015)","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"47_CR11","unstructured":"Long, M., Cao, Y., Wang, J., Jordan, M.: Learning transferable features with deep adaptation networks. In: ICML (2015)"},{"key":"47_CR12","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"478","DOI":"10.1007\/978-3-319-46723-8_55","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2016","author":"P Moeskops","year":"2016","unstructured":"Moeskops, P., Wolterink, J.M., Velden, B.H.M., Gilhuijs, K.G.A., Leiner, T., Viergever, M.A., Is\u030cgum, I.: Deep learning for multi-task medical image segmentation in multiple modalities. In: Ourselin, S., Joskowicz, L., Sabuncu, M.R., Unal, G., Wells, W. (eds.) MICCAI 2016. LNCS, vol. 9901, pp. 478\u2013486. Springer, Cham (2016). doi:10.1007\/978-3-319-46723-8_55"},{"issue":"5","key":"47_CR13","first-page":"1018","volume":"34","author":"A van Opbroek","year":"2015","unstructured":"van Opbroek, A., Ikram, M.A., Vernooij, M.W., De Bruijne, M.: Transfer learning improves supervised image segmentation across imaging protocols. TMI 34(5), 1018\u20131030 (2015)","journal-title":"TMI"},{"issue":"10","key":"47_CR14","doi-asserted-by":"publisher","first-page":"1345","DOI":"10.1109\/TKDE.2009.191","volume":"22","author":"SJ Pan","year":"2010","unstructured":"Pan, S.J., Yang, Q.: A survey on transfer learning. IEEE Trans. Knowl. Data Eng. 22(10), 1345\u20131359 (2010)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"issue":"2","key":"47_CR15","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1007\/s11682-012-9156-5","volume":"6","author":"M Shenton","year":"2012","unstructured":"Shenton, M., Hamoda, H., Schneiderman, J., Bouix, S., Pasternak, O., Rathi, Y., Vu, M.A., Purohit, M., Helmer, K., Koerte, I., et al.: A review of magnetic resonance imaging and diffusion tensor imaging findings in mild traumatic brain injury. Brain Imaging Behav. 6(2), 137\u2013192 (2012)","journal-title":"Brain Imaging Behav."},{"issue":"5","key":"47_CR16","first-page":"1285","volume":"35","author":"HC Shin","year":"2016","unstructured":"Shin, H.C., Roth, H.R., Gao, M., Lu, L., Xu, Z., Nogues, I., Yao, J., Mollura, D., Summers, R.M.: Deep convolutional neural networks for computer-aided detection: Cnn architectures, dataset characteristics and transfer learning. TMI 35(5), 1285\u20131298 (2016)","journal-title":"TMI"},{"key":"47_CR17","unstructured":"Tzeng, E., Hoffman, J., Zhang, N., Saenko, K., Darrell, T.: Deep domain confusion: maximizing for domain invariance. arXiv preprint (2014). arXiv:1412.3474"},{"issue":"10","key":"47_CR18","doi-asserted-by":"publisher","first-page":"2744","DOI":"10.1073\/pnas.1513198113","volume":"113","author":"S Ullman","year":"2016","unstructured":"Ullman, S., Assif, L., Fetaya, E., Harari, D.: Atoms of recognition in human and computer vision. Proc. Nat. Acad Sci. 113(10), 2744\u20132749 (2016)","journal-title":"Proc. Nat. Acad Sci."},{"issue":"11","key":"47_CR19","doi-asserted-by":"publisher","first-page":"1134","DOI":"10.1145\/1968.1972","volume":"27","author":"LG Valiant","year":"1984","unstructured":"Valiant, L.G.: A theory of the learnable. Commun. ACM 27(11), 1134\u20131142 (1984). http:\/\/doi.acm.org\/10.1145\/1968.1972","journal-title":"Commun. ACM"}],"container-title":["Lecture Notes in Computer Science","Information Processing in Medical Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-59050-9_47","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,5]],"date-time":"2024-03-05T14:05:55Z","timestamp":1709647555000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-59050-9_47"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"ISBN":["9783319590493","9783319590509"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-59050-9_47","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017]]},"assertion":[{"value":"23 May 2017","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IPMI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Information Processing in Medical Imaging","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Boone","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"USA","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2017","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 June 2017","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 June 2017","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ipmi2017","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ipmi2017.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}