{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T07:55:05Z","timestamp":1778658905005,"version":"3.51.4"},"publisher-location":"Cham","reference-count":8,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030322472","type":"print"},{"value":"9783030322489","type":"electronic"}],"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\/978-3-030-32248-9_19","type":"book-chapter","created":{"date-parts":[[2019,10,9]],"date-time":"2019-10-09T23:08:49Z","timestamp":1570662529000},"page":"164-172","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["Degenerative Adversarial NeuroImage Nets: Generating Images that Mimic Disease Progression"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0372-2677","authenticated-orcid":false,"given":"Daniele","family":"Ravi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2439-350X","authenticated-orcid":false,"given":"Daniel C.","family":"Alexander","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0203-3909","authenticated-orcid":false,"given":"Neil P.","family":"Oxtoby","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"name":"Alzheimer\u2019s Disease Neuroimaging Initiative","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,10,10]]},"reference":[{"key":"19_CR1","doi-asserted-by":"crossref","unstructured":"Bowles, C., et al.: Modelling the progression of Alzheimer\u2019s disease in MRI using generative adversarial networks. In: Medical Imaging 2018: Image Processing, vol. 10574, p. 105741K. International Society for Optics and Photonics (2018)","DOI":"10.1117\/12.2293256"},{"issue":"11","key":"19_CR2","first-page":"1417","volume":"25","author":"O Camara","year":"2006","unstructured":"Camara, O., et al.: Phenomenological model of diffuse global and regional atrophy using finite-element methods. TMI 25(11), 1417\u20131430 (2006)","journal-title":"TMI"},{"issue":"5","key":"19_CR3","first-page":"649","volume":"25","author":"B Kara\u00e7ali","year":"2006","unstructured":"Kara\u00e7ali, B., et al.: Simulation of tissue atrophy using a topology preserving transformation model. TMI 25(5), 649\u2013652 (2006)","journal-title":"TMI"},{"key":"19_CR4","doi-asserted-by":"publisher","first-page":"132","DOI":"10.3389\/fnins.2017.00132","volume":"11","author":"B Khanal","year":"2017","unstructured":"Khanal, B., et al.: Simulating longitudinal brain MRIs with known volume changes and realistic variations in image intensity. Front. Neurosci. 11, 132 (2017)","journal-title":"Front. Neurosci."},{"key":"19_CR5","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1007\/978-3-319-10443-0_8","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2014","author":"M Modat","year":"2014","unstructured":"Modat, M., et al.: Simulating neurodegeneration through longitudinal population analysis of structural and diffusion weighted MRI data. In: Golland, P., Hata, N., Barillot, C., Hornegger, J., Howe, R. (eds.) MICCAI 2014. LNCS, vol. 8675, pp. 57\u201364. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-10443-0_8"},{"issue":"4","key":"19_CR6","doi-asserted-by":"publisher","first-page":"371","DOI":"10.1097\/WCO.0000000000000460","volume":"30","author":"NP Oxtoby","year":"2017","unstructured":"Oxtoby, N.P., Alexander, D.C.: Imaging plus X: multimodal models of neurodegenerative disease. Curr. Opin. Neurol. 30(4), 371 (2017)","journal-title":"Curr. Opin. Neurol."},{"issue":"3","key":"19_CR7","doi-asserted-by":"publisher","first-page":"373","DOI":"10.1016\/j.media.2010.02.002","volume":"14","author":"S Sharma","year":"2010","unstructured":"Sharma, S., et al.: Evaluation of brain atrophy estimation algorithms using simulated ground-truth data. Med. Image Anal. 14(3), 373\u2013389 (2010)","journal-title":"Med. Image Anal."},{"key":"19_CR8","doi-asserted-by":"crossref","unstructured":"Zhang, Z., et al.: Age progression\/regression by conditional adversarial autoencoder. In: CVPR, pp. 5810\u20135818 (2017)","DOI":"10.1109\/CVPR.2017.463"}],"container-title":["Lecture Notes in Computer Science","Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2019"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-32248-9_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,10]],"date-time":"2024-10-10T00:22:22Z","timestamp":1728519742000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-32248-9_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030322472","9783030322489"],"references-count":8,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-32248-9_19","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"10 October 2019","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":"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":"13 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":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"miccai2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.miccai2019.org\/","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":"1730","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":"539","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":"31% - 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":"3.07","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":"6.31","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":"Yes","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"}]}}