{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,4,15]],"date-time":"2023-04-15T23:56:07Z","timestamp":1681602967128},"reference-count":25,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2017,9,12]],"date-time":"2017-09-12T00:00:00Z","timestamp":1505174400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"name":"National Natural Science Foundation of China under Grant","award":["61401473"],"award-info":[{"award-number":["61401473"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Process Lett"],"published-print":{"date-parts":[[2018,8]]},"DOI":"10.1007\/s11063-017-9704-5","type":"journal-article","created":{"date-parts":[[2017,9,12]],"date-time":"2017-09-12T20:21:56Z","timestamp":1505247716000},"page":"153-166","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Supervoxel Segmentation and Bias Correction of MR Image with Intensity Inhomogeneity"],"prefix":"10.1007","volume":"48","author":[{"given":"Jingjing","family":"Gao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Dai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chongjin","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie-Zhi","family":"Cheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoguang","family":"Tu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daiqiang","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bin","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yachun","family":"Gao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mei","family":"Xie","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2017,9,12]]},"reference":[{"issue":"8","key":"9704_CR1","doi-asserted-by":"crossref","first-page":"326","DOI":"10.1016\/j.neuroimage.2013.12.052","volume":"90","author":"BA Kirchhoff","year":"2014","unstructured":"Kirchhoff BA, Gordon BA, Head D (2014) Prefrontal gray matter volume mediates age effects on memory strategies. Neuroimage 90(8):326\u2013334","journal-title":"Neuroimage"},{"key":"9704_CR2","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1007\/978-3-319-02126-3_8","volume":"8159","author":"P Su","year":"2013","unstructured":"Su P, Yang J, Li H et al (2013) Superpixel-based segmentation of glioblastoma multiforme from multimodal mr images[M]. Multimodal Brain Image Anal 8159:74\u201383","journal-title":"Multimodal Brain Image Anal"},{"key":"9704_CR3","doi-asserted-by":"crossref","unstructured":"Ren X, Malik J (2003) Learning a Classification Model for Segmentation[C]. In: Proceedings of IEEE international conference on computer vision. IEEE, 2008, vol 1. pp 10\u201317","DOI":"10.1109\/ICCV.2003.1238308"},{"issue":"2","key":"9704_CR4","doi-asserted-by":"crossref","first-page":"474","DOI":"10.1109\/TMI.2011.2171705","volume":"31","author":"A Lucchi","year":"2012","unstructured":"Lucchi A, Smith K, Achanta R et al (2012) Supervoxel-based segmentation of mitochondria in em image stacks with learned shape features. IEEE Trans Med Imaging 31(2):474\u2013486","journal-title":"IEEE Trans Med Imaging"},{"issue":"5","key":"9704_CR5","doi-asserted-by":"crossref","first-page":"573","DOI":"10.1109\/LSP.2014.2364612","volume":"22","author":"Y Kong","year":"2015","unstructured":"Kong Y, Deng Y, Dai Q (2015) Discriminative clustering and feature selection for brain MRI segmentation. IEEE Signal Process Lett 22(5):573\u2013577","journal-title":"IEEE Signal Process Lett"},{"key":"9704_CR6","doi-asserted-by":"crossref","unstructured":"Verma N, Cowperthwaite MC, Markey MK (2013) Superpixels in brain MR image analysis. Conf Proc IEEE Eng Med Biol Soc 2013:1077\u20131080","DOI":"10.1109\/EMBC.2013.6609691"},{"issue":"11","key":"9704_CR7","doi-asserted-by":"crossref","first-page":"2274","DOI":"10.1109\/TPAMI.2012.120","volume":"34","author":"R Achanta","year":"2012","unstructured":"Achanta R, Shaji A, Smith K et al (2012) SLIC superpixels compared to state-of-the-art superpixel methods. IEEE Trans Pattern Anal Mach Intell 34(11):2274\u20132282","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"9704_CR8","doi-asserted-by":"crossref","unstructured":"Tian Z, Liu L Z, Fei B (2015) A supervoxel-based segmentation method for prostate MR images[C]. In: SPIE medical imaging. International society for optics and photonics","DOI":"10.1117\/12.2082255"},{"issue":"9","key":"9704_CR9","doi-asserted-by":"crossref","first-page":"1233","DOI":"10.1109\/TMI.2006.880668","volume":"25","author":"H Greenspan","year":"2006","unstructured":"Greenspan H, Ruf A, Goldberger J (2006) Constrained Gaussian mixture model framework for automatic segmentation of MR brain images. IEEE Trans Med Imaging 25(9):1233\u20131245","journal-title":"IEEE Trans Med Imaging"},{"key":"9704_CR10","unstructured":"Achanta R, Shaji A, Smith K et al (2010) Slic superpixels[R]"},{"issue":"10","key":"9704_CR11","doi-asserted-by":"crossref","first-page":"885","DOI":"10.1109\/42.811268","volume":"18","author":"K Leemput Van","year":"1999","unstructured":"Van Leemput K, Maes F, Vandermeulen D et al (1999) Automated model-based bias field correction of MR images of the brain. IEEE Trans Med Imaging 18(10):885","journal-title":"IEEE Trans Med Imaging"},{"issue":"11","key":"9704_CR12","doi-asserted-by":"crossref","first-page":"2974","DOI":"10.1587\/transinf.2014EDL8042","volume":"97","author":"H Xiong","year":"2014","unstructured":"Xiong H, Gao J, Zhu C et al (2014) An interleaved otsu segmentation for MR images with intensity inhomogeneity. Ieice Trans Inf Syst 97(11):2974\u20132978","journal-title":"Ieice Trans Inf Syst"},{"issue":"7","key":"9704_CR13","doi-asserted-by":"crossref","first-page":"913","DOI":"10.1016\/j.mri.2014.03.010","volume":"32","author":"C Li","year":"2014","unstructured":"Li C, Gore JC, Davatzikos C (2014) Multiplicative intrinsic component optimization (MICO) for MRI bias field estimation and tissue segmentation. Magn Reson Imaging 32(7):913\u2013923","journal-title":"Magn Reson Imaging"},{"key":"9704_CR14","doi-asserted-by":"crossref","unstructured":"Li C, Xu C, Anderson A W, et al (2009) MRI tissue classification and bias field estimation based on coherent local intensity clustering: a unified energy minimization framework[C]. In: International conference on information processing in medical imaging. Springer, Berlin, pp 288\u2013299","DOI":"10.1007\/978-3-642-02498-6_24"},{"key":"9704_CR15","unstructured":"Achanta R, Shaji A, Smith K et al (2010) SLIC superpixels. EDFL Technical Report no. 149300, June 2010"},{"key":"9704_CR16","doi-asserted-by":"crossref","unstructured":"Yu J, Yang X, Gao F, et al (2016) Deep multimodal distance metric learning using click constraints for image ranking. IEEE Trans Cybern","DOI":"10.1109\/TCYB.2016.2591583"},{"key":"9704_CR17","doi-asserted-by":"crossref","unstructured":"Li C, Gatenby C, Wang L, et al (2009) A robust parametric method for bias field estimation and segmentation of MR images[C]. In: IEEE conference on computer vision and pattern recognition, CVPR 2009. IEEE Xplore 2009, pp 218\u2013223","DOI":"10.1109\/CVPR.2009.5206553"},{"issue":"8","key":"9704_CR18","doi-asserted-by":"crossref","first-page":"1058","DOI":"10.1016\/j.mri.2014.03.006","volume":"32","author":"J Gao","year":"2014","unstructured":"Gao J, Li C, Feng C et al (2014) Non-locally regularized segmentation of multiple sclerosis lesion from multi-channel MRI data. Magn Reson Imaging 32(8):1058\u20131066","journal-title":"Magn Reson Imaging"},{"issue":"1","key":"9704_CR19","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1007\/s11517-014-1198-y","volume":"53","author":"M Xie","year":"2015","unstructured":"Xie M, Gao J, Zhu C et al (2015) A modified method for MRF segmentation and bias correction of MR image with intensity inhomogeneity. Med Biol Eng Comput 53(1):23\u201335","journal-title":"Med Biol Eng Comput"},{"key":"9704_CR20","first-page":"425","volume":"5","author":"CA Cocosco","year":"1997","unstructured":"Cocosco CA, Kollokian V, Kwan KS et al (1997) BrainWeb: online Interface to a 3D MRI simulated brain database. Neuroimage 5:425","journal-title":"Neuroimage"},{"key":"9704_CR21","unstructured":"Macqueen J (1967) Some methods for classification and analysis of multivariate observations[C]. In: Proceedings of berkeley symposium on mathematical statistics and probability, pp 281\u2013297"},{"issue":"5","key":"9704_CR22","doi-asserted-by":"crossref","first-page":"856","DOI":"10.1006\/nimg.2000.0730","volume":"13","author":"DW Shattuck","year":"2001","unstructured":"Shattuck DW, Sandor-Leahy SR, Schaper KA et al (2001) Magnetic resonance image tissue classification using a partial volume model. NeuroImage 13(5):856\u2013876","journal-title":"NeuroImage"},{"issue":"3","key":"9704_CR23","doi-asserted-by":"crossref","first-page":"839","DOI":"10.1016\/j.neuroimage.2005.02.018","volume":"26","author":"J Ashburner","year":"2005","unstructured":"Ashburner J, Friston KJ (2005) Unified segmentation. Neuroimage 26(3):839\u2013851","journal-title":"Neuroimage"},{"key":"9704_CR24","doi-asserted-by":"crossref","unstructured":"Pham DL (2001) Robust fuzzy segmentation of magnetic resonance images[C]. In: Fourteenth IEEE symposium on computer-based medical systems. IEEE Computer Society, p 127","DOI":"10.1109\/CBMS.2001.941709"},{"issue":"1","key":"9704_CR25","first-page":"216","volume":"61","author":"KJ Friston","year":"2013","unstructured":"Friston KJ (2013) Statistical parametric mapping: the analysis of functional brain images. Neurosurgery 61(1):216\u2013216","journal-title":"Neurosurgery"}],"container-title":["Neural Processing Letters"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11063-017-9704-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-017-9704-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-017-9704-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,10,3]],"date-time":"2019-10-03T11:29:01Z","timestamp":1570102141000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11063-017-9704-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,9,12]]},"references-count":25,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2018,8]]}},"alternative-id":["9704"],"URL":"https:\/\/doi.org\/10.1007\/s11063-017-9704-5","relation":{},"ISSN":["1370-4621","1573-773X"],"issn-type":[{"value":"1370-4621","type":"print"},{"value":"1573-773X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,9,12]]}}}