{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T15:31:42Z","timestamp":1742916702592,"version":"3.40.3"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030877347"},{"type":"electronic","value":"9783030877354"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-87735-4_5","type":"book-chapter","created":{"date-parts":[[2021,9,30]],"date-time":"2021-09-30T21:17:06Z","timestamp":1633036626000},"page":"44-53","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Unpaired MR Image Homogenisation by\u00a0Disentangled Representations and Its Uncertainty"],"prefix":"10.1007","author":[{"given":"Hongwei","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sunita","family":"Gopal","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anjany","family":"Sekuboyina","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianguo","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chen","family":"Niu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Carolin","family":"Pirkl","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jan","family":"Kirschke","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Benedikt","family":"Wiestler","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bjoern","family":"Menze","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,9,25]]},"reference":[{"key":"5_CR1","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1016\/j.neuroimage.2017.02.089","volume":"152","author":"DC Alexander","year":"2017","unstructured":"Alexander, D.C., et al.: Image quality transfer and applications in diffusion MRI. Neuroimage 152, 283\u2013298 (2017)","journal-title":"Neuroimage"},{"issue":"5","key":"5_CR2","doi-asserted-by":"publisher","first-page":"1661","DOI":"10.1002\/mp.12132","volume":"44","author":"K Bahrami","year":"2017","unstructured":"Bahrami, K., Shi, F., Rekik, I., Gao, Y., Shen, D.: 7T-guided super-resolution of 3T MRI. Med. Phys. 44(5), 1661\u20131677 (2017)","journal-title":"Med. Phys."},{"key":"5_CR3","doi-asserted-by":"crossref","unstructured":"Choi, Y., et al.: StarGAN: unified generative adversarial networks for multi-domain image-to-image translation. In: CVPR, pp. 8789\u20138797 (2018)","DOI":"10.1109\/CVPR.2018.00916"},{"key":"5_CR4","unstructured":"Glocker, B., Robinson, R., Castro, D.C., Dou, Q., Konukoglu, E.: Machine learning with multi-site imaging data: an empirical study on the impact of scanner effects. arXiv preprint arXiv:1910.04597 (2019)"},{"key":"5_CR5","unstructured":"Goodfellow, I.: Nips 2016 tutorial: generative adversarial networks. arXiv preprint arXiv:1701.00160 (2016)"},{"key":"5_CR6","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1007\/978-3-030-01246-5_3","volume-title":"Computer Vision \u2013 ECCV 2018","author":"H-Y Lee","year":"2018","unstructured":"Lee, H.-Y., Tseng, H.-Y., Huang, J.-B., Singh, M., Yang, M.-H.: Diverse image-to-image translation via disentangled representations. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11205, pp. 36\u201352. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01246-5_3"},{"key":"5_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"795","DOI":"10.1007\/978-3-030-32251-9_87","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2019","author":"H Li","year":"2019","unstructured":"Li, H., et al.: DiamondGAN: unified multi-modal generative adversarial networks for MRI sequences synthesis. In: Shen, D., et al. (eds.) MICCAI 2019. LNCS, vol. 11767, pp. 795\u2013803. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-32251-9_87"},{"key":"5_CR8","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1007\/978-3-030-33843-5_6","volume-title":"Machine Learning for Medical Image Reconstruction","author":"H Lin","year":"2019","unstructured":"Lin, H., et al.: Deep learning for low-field to high-field MR: image quality transfer with probabilistic decimation simulator. In: Knoll, F., Maier, A., Rueckert, D., Ye, J.C. (eds.) MLMIR 2019. LNCS, vol. 11905, pp. 58\u201370. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-33843-5_6"},{"key":"5_CR9","unstructured":"Liu, M.Y., Breuel, T., Kautz, J.: Unsupervised image-to-image translation networks. In: Advances in Neural Information Processing Systems, pp. 700\u2013708 (2017)"},{"issue":"2","key":"5_CR10","doi-asserted-by":"publisher","first-page":"e00422","DOI":"10.1002\/brb3.422","volume":"6","author":"AP Lysandropoulos","year":"2016","unstructured":"Lysandropoulos, A.P., et al.: Quantifying brain volumes for multiple sclerosis patients follow-up in clinical practice-comparison of 1.5 and 3 tesla magnetic resonance imaging. Brain Behav. 6(2), e00422 (2016)","journal-title":"Brain Behav."},{"key":"5_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"246","DOI":"10.1007\/978-3-319-46726-9_29","volume-title":"Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016","author":"O Oktay","year":"2016","unstructured":"Oktay, O., 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. LNCS, vol. 9902, pp. 246\u2013254. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46726-9_29"},{"issue":"14","key":"5_CR12","doi-asserted-by":"publisher","first-page":"145011","DOI":"10.1088\/1361-6560\/aacdd4","volume":"63","author":"J Park","year":"2018","unstructured":"Park, J., Hwang, D., Kim, K.Y., Kang, S.K., Kim, Y.K., Lee, J.S.: Computed tomography super-resolution using deep convolutional neural network. Phys. Med. Biol. 63(14), 145011 (2018)","journal-title":"Phys. Med. Biol."},{"key":"5_CR13","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1007\/978-3-642-40760-4_2","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2013","author":"W Shi","year":"2013","unstructured":"Shi, W., et al.: Cardiac image super-resolution with global correspondence using multi-atlas PatchMatch. In: Mori, K., Sakuma, I., Sato, Y., Barillot, C., Navab, N. (eds.) MICCAI 2013. LNCS, vol. 8151, pp. 9\u201316. Springer, Heidelberg (2013). https:\/\/doi.org\/10.1007\/978-3-642-40760-4_2"},{"key":"5_CR14","unstructured":"Siddharth, N., et al.: Learning disentangled representations with semi-supervised deep generative models. In: Advances in Neural Information Processing Systems, pp. 5925\u20135935 (2017)"},{"key":"5_CR15","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"611","DOI":"10.1007\/978-3-319-66182-7_70","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2017","author":"R Tanno","year":"2017","unstructured":"Tanno, R., et al.: Bayesian image quality transfer with CNNs: exploring uncertainty in dMRI super-resolution. In: Descoteaux, M., Maier-Hein, L., Franz, A., Jannin, P., Collins, D.L., Duchesne, S. (eds.) MICCAI 2017. LNCS, vol. 10433, pp. 611\u2013619. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-66182-7_70"},{"key":"5_CR16","doi-asserted-by":"publisher","first-page":"285","DOI":"10.1016\/j.neuroimage.2019.01.077","volume":"195","author":"CM Tax","year":"2019","unstructured":"Tax, C.M., et al.: Cross-scanner and cross-protocol diffusion MRI data harmonisation: a benchmark database and evaluation of algorithms. Neuroimage 195, 285\u2013299 (2019)","journal-title":"Neuroimage"},{"key":"5_CR17","unstructured":"Welander, P., Karlsson, S., Eklund, A.: Generative adversarial networks for image-to-image translation on multi-contrast MR images-a comparison of CycleGAN and unit. arXiv preprint arXiv:1806.07777 (2018)"},{"key":"5_CR18","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1007\/978-3-030-32245-8_29","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2019","author":"J Yang","year":"2019","unstructured":"Yang, J., Dvornek, N.C., Zhang, F., Chapiro, J., Lin, M.D., Duncan, J.S.: Unsupervised domain adaptation via disentangled representations: application to cross-modality liver segmentation. In: Shen, D., et al. (eds.) MICCAI 2019. LNCS, vol. 11765, pp. 255\u2013263. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-32245-8_29"},{"key":"5_CR19","unstructured":"Yurt, M., Dar, S.U.H., Erdem, A., Erdem, E., \u00c7ukur, T.: mustGAN: multi-stream generative adversarial networks for MR image synthesis. arXiv preprint arXiv:1909.11504 (2019)"},{"key":"5_CR20","doi-asserted-by":"crossref","unstructured":"Zhu, J.Y., et al.: Unpaired image-to-image translation using cycle-consistent adversarial networks. In: CVPR, pp. 2223\u20132232 (2017)","DOI":"10.1109\/ICCV.2017.244"}],"container-title":["Lecture Notes in Computer Science","Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Perinatal Imaging, Placental and Preterm Image Analysis"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-87735-4_5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,9,30]],"date-time":"2021-09-30T21:19:16Z","timestamp":1633036756000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-87735-4_5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030877347","9783030877354"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-87735-4_5","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"25 September 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"UNSURE","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Strasbourg","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"France","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1 October 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1 October 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"unsure2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/unsuremiccai.github.io\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}