{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,8]],"date-time":"2024-09-08T14:12:48Z","timestamp":1725804768881},"publisher-location":"Cham","reference-count":13,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319105802"},{"type":"electronic","value":"9783319105819"}],"license":[{"start":{"date-parts":[[2014,1,1]],"date-time":"2014-01-01T00:00:00Z","timestamp":1388534400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014]]},"DOI":"10.1007\/978-3-319-10581-9_28","type":"book-chapter","created":{"date-parts":[[2014,9,5]],"date-time":"2014-09-05T14:05:03Z","timestamp":1409925903000},"page":"223-230","source":"Crossref","is-referenced-by-count":2,"title":["Improved Reproducibility of Neuroanatomical Definitions through Diffeomorphometry and Complexity Reduction"],"prefix":"10.1007","author":[{"given":"Daniel","family":"Tward","sequence":"first","affiliation":[]},{"given":"Jorge","family":"Jovicich","sequence":"additional","affiliation":[]},{"given":"Andrea","family":"Soricelli","sequence":"additional","affiliation":[]},{"given":"Giovanni","family":"Frisoni","sequence":"additional","affiliation":[]},{"given":"Alain","family":"Trouv\u00e9","sequence":"additional","affiliation":[]},{"given":"Laurent","family":"Younes","sequence":"additional","affiliation":[]},{"given":"Michael","family":"Miller","sequence":"additional","affiliation":[]}],"member":"297","reference":[{"issue":"4","key":"28_CR1","doi-asserted-by":"publisher","first-page":"1402","DOI":"10.1016\/j.neuroimage.2012.02.084","volume":"61","author":"M. Reuter","year":"2012","unstructured":"Reuter, M., Schmansky, N.J., Rosas, H.D., Fischl, B.: Within-Subject Template Estimation for Unbiased Longitudinal Image Analysis. Neuroimage\u00a061(4), 1402\u20131418 (2012)","journal-title":"Neuroimage"},{"issue":"3","key":"28_CR2","doi-asserted-by":"publisher","first-page":"783","DOI":"10.1016\/j.neuroimage.2004.12.036","volume":"25","author":"J.G. Csernansky","year":"2005","unstructured":"Csernansky, J.G., et al.: Preclinical detection of Alzheimer\u2019s disease: hippocampal shape and volume predict dementia onset in the elderly. NeuroImage\u00a025(3), 783\u2013792 (2005)","journal-title":"NeuroImage"},{"key":"28_CR3","doi-asserted-by":"crossref","unstructured":"Gau, Y., Riklin-Raviv, T., Bouix, S.: Shape Analysis, A Field in Need of Careful Validation. Hum. Brain Mapp. (in press, 2014), doi:10.1002\/hbm.22525","DOI":"10.1002\/hbm.22525"},{"issue":"2","key":"28_CR4","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1023\/B:VISI.0000043755.93987.aa","volume":"61","author":"M.F. Beg","year":"2005","unstructured":"Beg, M.F., Miller, M.I., Trouv\u00e9, A., Younes, L.: Computing Large Deformation Metric Mappings via Geodesic Flows of Diffeomorphisms. Int. J. Comput. Vision\u00a061(2), 139\u2013157 (2005)","journal-title":"Int. J. Comput. Vision"},{"issue":"4","key":"28_CR5","doi-asserted-by":"publisher","first-page":"462","DOI":"10.1109\/TMI.2006.887380","volume":"26","author":"L. Wang","year":"2007","unstructured":"Wang, L., et al.: Large Deformation Diffeomorphism and Momentum Based Hippocampal Shape Discrimination in Dementia of the Alzheimer type. IEEE Trans. Med. Imaging\u00a026(4), 462\u2013470 (2007)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"28_CR6","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"132","DOI":"10.1007\/978-3-642-33415-3_17","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2012","author":"N. Singh","year":"2012","unstructured":"Singh, N., Wang, A.Y., Sankaranarayanan, P., Fletcher, P.T., Joshi, S.: Genetic, Structural and Functional Imaging Biomarkers for Early Detection of Conversion from MCI to AD. In: Ayache, N., Delingette, H., Golland, P., Mori, K. (eds.) MICCAI 2012, Part I. LNCS, vol.\u00a07510, pp. 132\u2013140. Springer, Heidelberg (2012)"},{"key":"28_CR7","doi-asserted-by":"crossref","unstructured":"Tang, X., et al.: Detecting, quantifying, and predicting. Hum. Brain Mapp. (2014), doi: 10.1002\/hbm.22431","DOI":"10.1002\/hbm.22431"},{"key":"28_CR8","doi-asserted-by":"crossref","unstructured":"Ma, J., Miller, M.I., Younes, L.: A bayesian generative model for surface template estimation. Int. J. Biomedical Imaging 2010, ID 974957, 14 pages (2010)","DOI":"10.1155\/2010\/974957"},{"issue":"2","key":"28_CR9","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1007\/s10851-005-3624-0","volume":"24","author":"M.I. Miller","year":"2006","unstructured":"Miller, M.I., Trouv\u00e9, A.: Geodesic Shooting for Computational Anatomy. Journal of Mathematical imaging and Vision\u00a024(2), 209\u2013228 (2006)","journal-title":"Journal of Mathematical imaging and Vision"},{"issue":"2","key":"28_CR10","doi-asserted-by":"publisher","first-page":"229","DOI":"10.1007\/s11263-011-0481-8","volume":"97","author":"F.-X. Vailard","year":"2011","unstructured":"Vailard, F.-X., Risser, L., Rueckert, D., Cotter, C.J.: Diffeomorphic 3D Image Registration via Geodesic Shooting Using an Efficient Adjoint Calculation. Int. J. Comput. Vision\u00a097(2), 229\u2013241 (2011)","journal-title":"Int. J. Comput. Vision"},{"issue":"1","key":"28_CR11","doi-asserted-by":"publisher","first-page":"161","DOI":"10.1007\/s11263-012-0556-1","volume":"101","author":"S. Durrleman","year":"2013","unstructured":"Durrleman, S., Allassonni\u00e8re, S., Joshi, S.: Sparse adaptive parameterization of variability in image ensembles. Int. J. Comput. Vision\u00a0101(1), 161\u2013183 (2013)","journal-title":"Int. J. Comput. Vision"},{"issue":"9","key":"28_CR12","doi-asserted-by":"publisher","first-page":"2206","DOI":"10.1175\/1520-0493(1991)119<2206:SLISFA>2.0.CO;2","volume":"119","author":"A. Staniforth","year":"1991","unstructured":"Staniforth, A., C\u00f4t\u00e9, J.: Semi-Lagrangian integration schemes for atmospheric models\u2014a review. Mon. Wea. Rev.\u00a0119(9), 2206\u20132223 (1991)","journal-title":"Mon. Wea. Rev."},{"key":"28_CR13","doi-asserted-by":"publisher","first-page":"472","DOI":"10.1016\/j.neuroimage.2013.05.007","volume":"83","author":"J. Jovicich","year":"2013","unstructured":"Jovicich, J., et al.: Brain morphometry reproducibility in multi-center 3 T MRI studies: A comparison of cross-sectional and longitudinal segmentations. Neuroimage\u00a083, 472\u2013484 (2013)","journal-title":"Neuroimage"}],"container-title":["Lecture Notes in Computer Science","Machine Learning in Medical Imaging"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-10581-9_28","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,27]],"date-time":"2019-05-27T19:55:39Z","timestamp":1558986939000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-10581-9_28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014]]},"ISBN":["9783319105802","9783319105819"],"references-count":13,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-10581-9_28","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2014]]}}}