{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,8]],"date-time":"2025-07-08T04:04:00Z","timestamp":1751947440718,"version":"3.41.2"},"publisher-location":"Cham","reference-count":22,"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_30","type":"book-chapter","created":{"date-parts":[[2018,9,12]],"date-time":"2018-09-12T23:26:09Z","timestamp":1536794769000},"page":"258-266","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Structured Deep Generative Model of fMRI Signals for Mental Disorder Diagnosis"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0642-4800","authenticated-orcid":false,"given":"Takashi","family":"Matsubara","sequence":"first","affiliation":[]},{"given":"Tetsuo","family":"Tashiro","sequence":"additional","affiliation":[]},{"given":"Kuniaki","family":"Uehara","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,9,13]]},"reference":[{"issue":"11","key":"30_CR1","doi-asserted-by":"publisher","first-page":"1440","DOI":"10.1038\/nn.3839","volume":"17","author":"TJ Sejnowski","year":"2014","unstructured":"Sejnowski, T.J., et al.: Putting big data to good use in neuroscience. Nat. Neurosci. 17(11), 1440\u20131441 (2014)","journal-title":"Nat. Neurosci."},{"issue":"3","key":"30_CR2","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1067\/mcp.2001.113989","volume":"69","author":"Group, B.D.W.","year":"2001","unstructured":"Group, B.D.W.: Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clinic. Pharmacol. Ther. 69(3), 89\u201395 (2001)","journal-title":"Clinic. Pharmacol. Ther."},{"issue":"4","key":"30_CR3","doi-asserted-by":"publisher","first-page":"3110","DOI":"10.1016\/j.neuroimage.2009.11.011","volume":"49","author":"H Shen","year":"2010","unstructured":"Shen, H., et al.: Discriminative analysis of resting-state functional connectivity patterns of schizophrenia using low dimensional embedding of fMRI. NeuroImage 49(4), 3110\u20133121 (2010)","journal-title":"NeuroImage"},{"issue":"7","key":"30_CR4","doi-asserted-by":"publisher","first-page":"1729","DOI":"10.1109\/TMI.2016.2527717","volume":"35","author":"E Castro","year":"2016","unstructured":"Castro, E., et al.: Deep independence network analysis of structural brain imaging: application to schizophrenia. IEEE Trans. Med. Imaging 35(7), 1729\u20131740 (2016)","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"7","key":"30_CR5","doi-asserted-by":"publisher","first-page":"11254","DOI":"10.1038\/ncomms11254","volume":"7","author":"N Yahata","year":"2016","unstructured":"Yahata, N., et al.: A small number of abnormal brain connections predicts adult autism spectrum disorder. Nat. Commun. 7(7), 11254 (2016)","journal-title":"Nat. Commun."},{"key":"30_CR6","doi-asserted-by":"publisher","first-page":"292","DOI":"10.1016\/j.neuroimage.2016.01.005","volume":"129","author":"HI Suk","year":"2016","unstructured":"Suk, H.I., et al.: State-space model with deep learning for functional dynamics estimation in resting-state fMRI. NeuroImage 129, 292\u2013307 (2016)","journal-title":"NeuroImage"},{"unstructured":"Chen, P.H., et al.: A Reduced-Dimension fMRI Shared Response Model. In: NIPS. (2015) 460\u2013468","key":"30_CR7"},{"unstructured":"Tashiro, T., et al.: Deep neural generative model for fMRI image based diagnosis of mental disorder. In: NOLTA (2017)","key":"30_CR8"},{"doi-asserted-by":"crossref","unstructured":"Lasserre, J., et al.: Principled hybrids of generative and discriminative models. In: CVPR, pp. 87\u201394 (2006)","key":"30_CR9","DOI":"10.1109\/CVPR.2006.227"},{"key":"30_CR10","doi-asserted-by":"publisher","first-page":"736","DOI":"10.1016\/j.neuroimage.2016.10.045","volume":"147","author":"A Abraham","year":"2017","unstructured":"Abraham, A., et al.: Deriving reproducible biomarkers from multi-site resting-state data: an autism-based example. NeuroImage 147, 736\u2013745 (2017)","journal-title":"NeuroImage"},{"key":"30_CR11","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1016\/j.neunet.2014.09.003","volume":"61","author":"J Schmidhuber","year":"2015","unstructured":"Schmidhuber, J.: Deep learning in neural networks: an overview. Neur. Netw. 61, 85\u2013117 (2015)","journal-title":"Neur. Netw."},{"issue":"4","key":"30_CR12","doi-asserted-by":"publisher","first-page":"1132","DOI":"10.1109\/TBME.2014.2372011","volume":"62","author":"S Liu","year":"2015","unstructured":"Liu, S., et al.: Multimodal neuroimaging feature learning for multiclass diagnosis of Alzheimer\u2019s disease. IEEE Trans. Biomed. Eng. 62(4), 1132\u20131140 (2015)","journal-title":"IEEE Trans. Biomed. Eng."},{"unstructured":"Kingma, D.P., et al.: Semi-supervised learning with deep generative models. In: NIPS, pp. 3581\u20133589 (2014)","key":"30_CR13"},{"unstructured":"Maal\u00f8e, L., et al.: Auxiliary deep generative models. In: ICML, vol. 48, pp. 1445\u20131453 (2015)","key":"30_CR14"},{"key":"30_CR15","doi-asserted-by":"publisher","first-page":"S199","DOI":"10.1016\/j.neuroimage.2008.11.007","volume":"45","author":"F Pereira","year":"2009","unstructured":"Pereira, F., et al.: Machine learning classifiers and fMRI: a tutorial overview. NeuroImage 45, S199\u2013S209 (2009)","journal-title":"NeuroImage"},{"key":"30_CR16","first-page":"362","volume":"I","author":"NC Dvornek","year":"2017","unstructured":"Dvornek, N.C., et al.: Identifying autism from resting-state fMRI using long short-term memory networks. MLM I, 362\u2013370 (2017)","journal-title":"MLM"},{"unstructured":"Ba, J.L., et al.: Layer normalization, pp. 1\u201314. arXiv (2016)","key":"30_CR17"},{"unstructured":"Nair, V., Hinton, G.E.: Rectified linear units improve restricted Boltzmann machines. In: ICML, pp. 807\u2013814 (2010)","key":"30_CR18"},{"key":"30_CR19","first-page":"1929","volume":"15","author":"N Srivastava","year":"2014","unstructured":"Srivastava, N., et al.: Dropout: a simple way to prevent neural networks from overfitting. JMLR 15, 1929\u20131958 (2014)","journal-title":"JMLR"},{"unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. In: ICLR, pp. 1\u201315 (2015)","key":"30_CR20"},{"issue":"1","key":"30_CR21","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1006\/nimg.2001.0978","volume":"15","author":"N Tzourio-Mazoyer","year":"2002","unstructured":"Tzourio-Mazoyer, N., et al.: Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. NeuroImage 15(1), 273\u2013289 (2002)","journal-title":"NeuroImage"},{"issue":"2","key":"30_CR22","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1016\/j.biopsych.2008.01.003","volume":"64","author":"NC Andreasen","year":"2008","unstructured":"Andreasen, N.C., Pierson, R.: The role of the cerebellum in schizophrenia. Biol. Psychiatry 64(2), 81\u201388 (2008)","journal-title":"Biol. Psychiatry"}],"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_30","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,7]],"date-time":"2025-07-07T04:21:56Z","timestamp":1751862116000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-00931-1_30"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030009304","9783030009311"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-00931-1_30","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"}]}}