{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,5]],"date-time":"2024-09-05T00:21:15Z","timestamp":1725495675301},"publisher-location":"Berlin, Heidelberg","reference-count":18,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783540757566"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"DOI":"10.1007\/978-3-540-75757-3_107","type":"book-chapter","created":{"date-parts":[[2007,11,21]],"date-time":"2007-11-21T09:52:10Z","timestamp":1195638730000},"page":"883-890","source":"Crossref","is-referenced-by-count":19,"title":["Clinical Neonatal Brain MRI Segmentation Using Adaptive Nonparametric Data Models and Intensity-Based Markov Priors"],"prefix":"10.1007","author":[{"given":"Zhuang","family":"Song","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Suyash P.","family":"Awate","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniel J.","family":"Licht","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"James C.","family":"Gee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","reference":[{"issue":"6","key":"107_CR1","doi-asserted-by":"publisher","first-page":"459","DOI":"10.1007\/BF00340123","volume":"31","author":"M. Knaap van der","year":"1990","unstructured":"van der Knaap, M., Valik, J.: MR imaging of the various stages of normal myelination during the first year of life. Neuroradiology\u00a031(6), 459\u2013470 (1990)","journal-title":"Neuroradiology"},{"key":"107_CR2","unstructured":"Dietrich, R.: Maturation, Myelination, and Dysmyelination. In: Magnetic Resonance Imaging. Mosby. pp. 1425\u20131447 (1999)"},{"issue":"3","key":"107_CR3","doi-asserted-by":"publisher","first-page":"311","DOI":"10.1007\/s10545-005-5952-z","volume":"28","author":"A. Barkovich","year":"2005","unstructured":"Barkovich, A.: Magnetic resonance techniques in the assessment of myelin and myelination. J Inherit Metab Dis.\u00a028(3), 311\u2013343 (2005)","journal-title":"J Inherit Metab Dis."},{"issue":"5","key":"107_CR4","doi-asserted-by":"publisher","first-page":"457","DOI":"10.1016\/j.media.2005.05.007","volume":"9","author":"M. Prastawa","year":"2005","unstructured":"Prastawa, M., Gilmore, J., Lin, W., Gerig, G.: Automatic segmentation of MR images of the developing newborn brain. Med Image Anal.\u00a09(5), 457\u2013466 (2005)","journal-title":"Med Image Anal."},{"key":"107_CR5","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"831","DOI":"10.1007\/11866763_102","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2006","author":"Z. Song","year":"2006","unstructured":"Song, Z., Tustison, N., Avants, B., Gee, J.: Integrated graph cuts for brain mri segmentation. In: Larsen, R., Nielsen, M., Sporring, J. (eds.) MICCAI 2006. LNCS, vol.\u00a04191, pp. 831\u2013838. Springer, Heidelberg (2006)"},{"key":"107_CR6","doi-asserted-by":"publisher","first-page":"897","DOI":"10.1109\/42.811270","volume":"18","author":"K.V. Leemput","year":"1999","unstructured":"Leemput, K.V., Maes, F., Vandermeulen, D., Seutens, P.: Automated model-based tissue classification of MR images of the brain. IEEE Tr. Med. Imaging\u00a018, 897\u2013908 (1999)","journal-title":"IEEE Tr. Med. Imaging"},{"issue":"9","key":"107_CR7","doi-asserted-by":"publisher","first-page":"1233","DOI":"10.1109\/TMI.2006.880668","volume":"25","author":"H. Greenspan","year":"2006","unstructured":"Greenspan, H., Ruf, A., Goldberger, J.: Constrained gaussian mixture model framework for automatic segmentation of MR brain images. IEEE Trans. Medical Imaging\u00a025(9), 1233\u20131245 (2006)","journal-title":"IEEE Trans. Medical Imaging"},{"issue":"5","key":"107_CR8","doi-asserted-by":"publisher","first-page":"726","DOI":"10.1016\/j.media.2006.07.002","volume":"10","author":"S. Awate","year":"2006","unstructured":"Awate, S., Tasdizen, T., Foster, N., Whitaker, R.: Adaptive, nonparametric markov modeling for unsupervised, MRI brain-tissue classification. Medical Image Analysis\u00a010(5), 726\u2013739 (2006)","journal-title":"Medical Image Analysis"},{"key":"107_CR9","doi-asserted-by":"crossref","unstructured":"Awate, S.P., Gee, J.C.: A fuzzy, nonparametric segmentation framework for DTI and MRI analysis. In: Proc. Info. Proc. in Med. Imag (IPMI) (to appear, 2007)","DOI":"10.1007\/978-3-540-73273-0_25"},{"key":"107_CR10","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1023\/A:1009715923555","volume":"2","author":"C. Burges","year":"1998","unstructured":"Burges, C.: A tutorial on support vector machines for pattern recognition. Data Mining and Knowledge Discovery\u00a02, 121\u2013167 (1998)","journal-title":"Data Mining and Knowledge Discovery"},{"issue":"11","key":"107_CR11","doi-asserted-by":"publisher","first-page":"1222","DOI":"10.1109\/34.969114","volume":"23","author":"Y. Boykov","year":"2001","unstructured":"Boykov, Y., Veksler, O., Zabih, R.: Fast approximate energy minimization via graph cuts. IEEE Trans. Pattern Anal. Machine Intell.\u00a023(11), 1222\u20131239 (2001)","journal-title":"IEEE Trans. Pattern Anal. Machine Intell."},{"issue":"1","key":"107_CR12","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1214\/aos\/1176346053","volume":"11","author":"Y. Chow","year":"1983","unstructured":"Chow, Y., Geman, S., Wu, L.: Consistent cross-validated density estimation. Annals of Statistics\u00a011(1), 25\u201338 (1983)","journal-title":"Annals of Statistics"},{"key":"107_CR13","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1162\/15324430152733142","volume":"1","author":"R. Collobert","year":"2001","unstructured":"Collobert, R., Bengio, S.: Svmtorch: Support vector machines for large-scale regression problems. Journal of machine learning research\u00a01, 143\u2013160 (2001)","journal-title":"Journal of machine learning research"},{"key":"107_CR14","volume-title":"Advances in Large Margin Classifiers","author":"J. Platt","year":"1999","unstructured":"Platt, J.: Probabilistic outputs for support vector machines and comparison to regularized likelihood methods. In: Advances in Large Margin Classifiers, MIT Press, Cambridge (1999)"},{"key":"107_CR15","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1007\/11866565_25","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2006","author":"N. Weisenfeld","year":"2006","unstructured":"Weisenfeld, N., Mewes, A., Warfield, S.: Highly accurate segmentation of brain tissue and subcortical gray matter from newborn mri. In: Larsen, R., Nielsen, M., Sporring, J. (eds.) MICCAI 2006. LNCS, vol.\u00a04190, pp. 199\u2013206. Springer, Heidelberg (2006)"},{"key":"107_CR16","doi-asserted-by":"crossref","first-page":"S139","DOI":"10.1016\/j.neuroimage.2004.07.010","volume":"1","author":"B. Avants","year":"2004","unstructured":"Avants, B., Gee, J.: Geodesic estimation for large deformation anatomical shape and intensity averaging. Neuroimage\u00a0Suppl. 1, S139\u2013150 (2004)","journal-title":"Neuroimage Suppl"},{"issue":"12","key":"107_CR17","doi-asserted-by":"publisher","first-page":"1398","DOI":"10.1109\/42.974934","volume":"20","author":"B. Likar","year":"2001","unstructured":"Likar, B., Viergever, M.A., Pernus, F.: Retrospective correction of MR intensity inhomogeneity by information minimization. IEEE Trans. Med. Imaging\u00a020(12), 1398\u20131410 (2001)","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"5","key":"107_CR18","doi-asserted-by":"publisher","first-page":"889","DOI":"10.1109\/83.841534","volume":"9","author":"J. Stark","year":"2000","unstructured":"Stark, J.: Adaptive image contrast enhancement using generalizations of histogram equalization. IEEE Trans. Image Processing\u00a09(5), 889\u2013896 (2000)","journal-title":"IEEE Trans. Image Processing"}],"container-title":["Lecture Notes in Computer Science","Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2007"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-540-75757-3_107.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,4,27]],"date-time":"2021-04-27T06:31:39Z","timestamp":1619505099000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-540-75757-3_107"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[null]]},"ISBN":["9783540757566"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-540-75757-3_107","relation":{},"subject":[]}}