{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T23:05:10Z","timestamp":1780095910607,"version":"3.54.0"},"reference-count":41,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2013,7,17]],"date-time":"2013-07-17T00:00:00Z","timestamp":1374019200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int J CARS"],"published-print":{"date-parts":[[2014,3]]},"DOI":"10.1007\/s11548-013-0922-7","type":"journal-article","created":{"date-parts":[[2013,7,16]],"date-time":"2013-07-16T06:51:29Z","timestamp":1373957489000},"page":"241-253","source":"Crossref","is-referenced-by-count":126,"title":["Brain tumor detection and segmentation in a CRF (conditional random fields) framework with pixel-pairwise affinity and superpixel-level features"],"prefix":"10.1007","volume":"9","author":[{"given":"Wei","family":"Wu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Albert Y. C.","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liang","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jason J.","family":"Corso","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2013,7,17]]},"reference":[{"key":"922_CR1","doi-asserted-by":"crossref","unstructured":"Liu J, Udupa JK, Odhner D, Hackney D, Moonis G (2005) A system for brain tumor volume estimation via MR imaging and fuzzy connectedness. Comput Med Imaging Graphics 29(1):21\u201334","DOI":"10.1016\/j.compmedimag.2004.07.008"},{"issue":"1","key":"922_CR2","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1109\/42.668698","volume":"17","author":"JG Sled","year":"1998","unstructured":"Sled JG, Zijdenbos AP, Evans AC (1998) A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Trans Med Imaging 17(1):87\u201397","journal-title":"IEEE Trans Med Imaging"},{"issue":"2","key":"922_CR3","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1016\/j.media.2005.09.004","volume":"10","author":"B Belaroussi","year":"2006","unstructured":"Belaroussi B, Milles J, Carme S, Zhu YM, Benoit-Cattin H (2006) Intensity non-uniformity correction in MRI: existing methods and their validation. Med Image Anal 10(2):234","journal-title":"Med Image Anal"},{"issue":"5","key":"922_CR4","doi-asserted-by":"crossref","first-page":"561","DOI":"10.1109\/TMI.2004.843256","volume":"24","author":"A Madabhushi","year":"2005","unstructured":"Madabhushi A, Udupa JK (2005) Interplay between intensity standardization and inhomogeneity correction in MR image processing. IEEE Trans Med Imaging 24(5):561\u2013576","journal-title":"IEEE Trans Med Imaging"},{"key":"922_CR5","doi-asserted-by":"crossref","unstructured":"Patel MR, Tse V (2004) Diagnosis and staging of brain tumors. Semin Roentgenol 39(3):347\u2013360","DOI":"10.1016\/j.ro.2004.05.005"},{"issue":"3","key":"922_CR6","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1016\/j.media.2004.06.007","volume":"8","author":"M Prastawa","year":"2004","unstructured":"Prastawa M, Bullitt E, Ho S, Gerig G (2004) A brain tumor segmentation framework based on outlier detection. Med Image Anal 8(3):275\u2013283","journal-title":"Med Image Anal"},{"issue":"2","key":"922_CR7","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1016\/0730-725X(94)00093-I","volume":"13","author":"W Phillips","year":"1995","unstructured":"Phillips W, Velthuizen R, Phuphanich S, Hall L, Clarke L, Silbiger M (1995) Application of fuzzy c-means segmentation technique for tissue differentiation in MR images of a hemorrhagic glioblastoma multiforme. Magn Reson Imaging 13(2):277\u2013290","journal-title":"Magn Reson Imaging"},{"issue":"2","key":"922_CR8","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1109\/42.700731","volume":"17","author":"MC Clark","year":"1998","unstructured":"Clark MC, Hall LO, Goldgof DB, Velthuizen R, Murtagh FR, Silbiger MS (1998) Automatic tumor segmentation using knowledge-based techniques. IEEE Trans Med Imaging 17(2):187\u2013201","journal-title":"IEEE Trans Med Imaging"},{"issue":"1\u20133","key":"922_CR9","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/S0933-3657(00)00073-7","volume":"21","author":"LM Fletcher-Heath","year":"2001","unstructured":"Fletcher-Heath LM, Hall LO, Goldgof DB, Murtagh FR (2001) Automatic segmentation of non-enhancing brain tumors in magnetic resonance images. Artif Intell Med 21(1\u20133):43\u201363","journal-title":"Artif Intell Med"},{"issue":"1","key":"922_CR10","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/S1361-8415(00)00003-7","volume":"4","author":"SK Warfield","year":"2000","unstructured":"Warfield SK, Kaus M, Jolesz FA, Kikinis R (2000) Adaptive, template moderated, spatially varying statistical classification. Med Image Anal 4(1):43\u201355","journal-title":"Med Image Anal"},{"issue":"2","key":"922_CR11","doi-asserted-by":"crossref","first-page":"586","DOI":"10.1148\/radiology.218.2.r01fe44586","volume":"218","author":"MR Kaus","year":"2001","unstructured":"Kaus MR, Warfield SK, Nabavi A, Black PM, Jolesz FA, Kikinis R (2001) Automated segmentation of MR images of Brain Tumors1. Radiology 218(2):586\u2013591","journal-title":"Radiology"},{"issue":"12","key":"922_CR12","doi-asserted-by":"crossref","first-page":"1341","DOI":"10.1016\/S1076-6332(03)00506-3","volume":"10","author":"M Prastawa","year":"2003","unstructured":"Prastawa M, Bullitt E, Moon N, Van Leemput K, Gerig G (2003) Automatic brain tumor segmentation by subject specific modification of atlas priors. Acad Radiol 10(12):1341\u20131348","journal-title":"Acad Radiol"},{"issue":"4","key":"922_CR13","doi-asserted-by":"crossref","first-page":"429","DOI":"10.1109\/42.511747","volume":"15","author":"W Wells III","year":"1996","unstructured":"Wells W III, Grimson WEL, Kikinis R, Jolesz FA (1996) Adaptive segmentation of MRI data. IEEE Trans Med Imaging 15(4):429\u2013442","journal-title":"IEEE Trans Med Imaging"},{"issue":"3","key":"922_CR14","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1109\/42.585758","volume":"16","author":"R Guillemaud","year":"1997","unstructured":"Guillemaud R, Brady M (1997) Estimating the bias field of MR images. IEEE Trans Med Imaging 16(3):238\u2013251","journal-title":"IEEE Trans Med Imaging"},{"issue":"5","key":"922_CR15","doi-asserted-by":"crossref","first-page":"629","DOI":"10.1109\/TMI.2007.912817","volume":"27","author":"JJ Corso","year":"2008","unstructured":"Corso JJ, Sharon E, Dube S, El-Saden S, Sinha U, Yuille A (2008) Efficient multilevel brain tumor segmentation with integrated bayesian model classification. IEEE Trans Med Imaging 27(5):629\u2013640","journal-title":"IEEE Trans Med Imaging"},{"key":"922_CR16","unstructured":"Zhou J, Chan K, Chong V, Krishnan S (2006) Extraction of brain tumor from MR images using one-class support vector machine. In: 27th annual international conference of the engineering in medicine and biology society, 2005. IEEE-EMBS 2005. pp 6411\u20136414"},{"key":"922_CR17","first-page":"070","volume":"9","author":"X Xuan","year":"2008","unstructured":"Xuan X, Liao Q (2008) Automated MRI brain rumor segmentation based on feature extraction. Comput Eng 9:070","journal-title":"Comput Eng"},{"key":"922_CR18","doi-asserted-by":"crossref","unstructured":"Corso J, Yuille A, Sicotte N, Toga A (2007) Detection and segmentation of pathological structures by the extended graph-shifts algorithm. In: Medical Image Computing and Computer-Assisted Intervention\u2014MICCAI. pp 985\u2013993","DOI":"10.1007\/978-3-540-75757-3_119"},{"issue":"5","key":"922_CR19","doi-asserted-by":"crossref","first-page":"1651","DOI":"10.1214\/aos\/1024691352","volume":"26","author":"RE Schapire","year":"1998","unstructured":"Schapire RE, Freund Y, Bartlett P, Lee WS (1998) Boosting the margin: a new explanation for the effectiveness of voting methods. Ann Stat 26(5):1651\u20131686","journal-title":"Ann Stat"},{"issue":"18","key":"922_CR20","doi-asserted-by":"crossref","first-page":"3583","DOI":"10.1093\/bioinformatics\/bth447","volume":"20","author":"M Dettling","year":"2004","unstructured":"Dettling M (2004) BagBoosting for tumor classification with gene expression data. Bioinformatics 20(18):3583\u20133593","journal-title":"Bioinformatics"},{"issue":"1","key":"922_CR21","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman L (2001) Random forests. Mach Learn 45(1):5\u201332","journal-title":"Mach Learn"},{"key":"922_CR22","doi-asserted-by":"crossref","unstructured":"Zikic D, Glocker B, Konukoglu E, Criminisi A, Demiralp C, Shotton J, Thomas O, Das T, Jena R, Price S (2012) Decision forests for tissue-specific segmentation of high-grade gliomas in multi-channel MR. In: Medical Image Computing and Computer-Assisted Intervention\u2014MICCAI. Lecture notes in computer science, vol 7512. pp 369\u2013376","DOI":"10.1007\/978-3-642-33454-2_46"},{"issue":"1","key":"922_CR23","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.artint.2004.05.009","volume":"159","author":"H Liu","year":"2004","unstructured":"Liu H, Motoda H, Yu L (2004) A selective sampling approach to active feature selection. Artif Intell 159(1):49\u201374","journal-title":"Artif Intell"},{"key":"922_CR24","doi-asserted-by":"crossref","unstructured":"Fern\u00e1ndez A, Garc\u00eda S, Herrera F (2011) Addressing the classification with imbalanced data: open problems and new challenges on class distribution. In: Hybrid artificial intelligent systems. Lecture notes in computer science, vol 6678. pp 1\u201310","DOI":"10.1007\/978-3-642-21219-2_1"},{"key":"922_CR25","volume-title":"Markov random field modeling in computer vision","author":"SZ Li","year":"1995","unstructured":"Li SZ (1995) Markov random field modeling in computer vision. Springer, New York"},{"issue":"1","key":"922_CR26","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1109\/42.906424","volume":"20","author":"Y Zhang","year":"2001","unstructured":"Zhang Y, Brady M, Smith S (2001) Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. IEEE Trans Med Imaging 20(1):45\u201357","journal-title":"IEEE Trans Med Imaging"},{"key":"922_CR27","doi-asserted-by":"crossref","unstructured":"Lee CH, Schmidt M, Murtha A, Bistritz A, Sander J, Greiner R (2005) Segmenting brain tumors with conditional random fields and support vector machines. In: Computer vision for biomedical, image applications. Lecture notes in computer science, vol 3765. pp 469\u2013478","DOI":"10.1007\/11569541_47"},{"issue":"2","key":"922_CR28","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1023\/B:VISI.0000022288.19776.77","volume":"59","author":"PF Felzenszwalb","year":"2004","unstructured":"Felzenszwalb PF, Huttenlocher DP (2004) Efficient graph-based image segmentation. Int J Comput Vis 59(2):167\u2013181","journal-title":"Int J Comput Vis"},{"key":"922_CR29","unstructured":"Xu C, Corso JJ (2002) Evaluation of super-voxel methods for early video processing. In: IEEE conference on computer vision and pattern recognition (CVPR) 2012, pp 1202\u20131209"},{"key":"922_CR30","doi-asserted-by":"crossref","unstructured":"Bauer S, Nolte L-P, Reyes M (2011) Fully automatic segmentation of brain tumor images using support vector machine classification in combination with hierarchical conditional random field regularization. In: Medical Image Computing and Computer-Assisted Intervention\u2014MICCAI 2011. Springer, pp 354\u2013361","DOI":"10.1007\/978-3-642-23626-6_44"},{"issue":"3","key":"922_CR31","first-page":"61","volume":"10","author":"J Platt","year":"1999","unstructured":"Platt J (1999) Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods. Adv Large Margin Class 10(3):61\u201374","journal-title":"Adv Large Margin Class"},{"key":"922_CR32","doi-asserted-by":"crossref","unstructured":"Ren X, Malik J (2003) Learning a classification model for segmentation. In: Proceedings of the ninth IEEE international conference on computer vision, 2003. pp 10\u201317","DOI":"10.1109\/ICCV.2003.1238308"},{"key":"922_CR33","doi-asserted-by":"crossref","unstructured":"Manjunath BS, Ma WY (1996) Texture features for browsing and retrieval of image data. IEEE Trans Pattern Anal Mach Intell 18(8):837\u2013842","DOI":"10.1109\/34.531803"},{"key":"922_CR34","doi-asserted-by":"crossref","unstructured":"Lee TS (1996) Image representation using 2D Gabor wavelets. IEEE Trans Pattern Anal Mach Intell 18(10):959\u2013971","DOI":"10.1109\/34.541406"},{"key":"922_CR35","doi-asserted-by":"crossref","unstructured":"Boykov Y, Veksler O, Zabih R (2001) Fast approximate energy minimization via graph cuts. IEEE Trans Pattern Anal Mach Intell 23(11):1222\u20131239","DOI":"10.1109\/34.969114"},{"issue":"9","key":"922_CR36","doi-asserted-by":"crossref","first-page":"1124","DOI":"10.1109\/TPAMI.2004.60","volume":"26","author":"Y Boykov","year":"2004","unstructured":"Boykov Y, Kolmogorov V (2004) An experimental comparison of min-cut\/max-flow algorithms for energy minimization in vision. IEEE Trans Pattern Anal Mach Intell 26(9):1124\u20131137","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"2","key":"922_CR37","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1109\/TPAMI.2004.1262177","volume":"26","author":"V Kolmogorov","year":"2004","unstructured":"Kolmogorov V, Zabin R (2004) What energy functions can be minimized via graph cuts? IEEE Trans Pattern Anal Mach Intell 26(2):147\u2013159","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"922_CR38","unstructured":"Zabih RD, Veksler O, Boykov Y (2004) System and method for fast approximate energy minimization via graph cuts. U. S. Patent 6,744, 923 [p]. 1 June 2004"},{"issue":"1","key":"922_CR39","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11263-011-0437-z","volume":"96","author":"A Delong","year":"2012","unstructured":"Delong A, Osokin A, Isack HN, Boykov Y (2012) Fast approximate energy minimization with label costs. Int J Comput Vis 96(1):1\u201327","journal-title":"Int J Comput Vis"},{"issue":"7015","key":"922_CR40","doi-asserted-by":"crossref","first-page":"396","DOI":"10.1038\/nature03128","volume":"432","author":"SK Singh","year":"2004","unstructured":"Singh SK, Hawkins C, Clarke ID, Squire JA, Bayani J, Hide T, Henkelman RM, Cusimano MD, Dirks PB (2004) Identification of human brain tumour initiating cells. Nature 432(7015):396\u2013401","journal-title":"Nature"},{"key":"922_CR41","unstructured":"Zikic D, Glocker B, Konukoglu E, Shotton J, Criminisi A, Ye DH, Demiralp C, Thomas OM, Das T, Jena R, Price SJ (2012) Context-sensitive classification forests for segmentation of brain tumor tissues. In: Proceedings of MICCAI-BRATS (2012)"}],"container-title":["International Journal of Computer Assisted Radiology and Surgery"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11548-013-0922-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11548-013-0922-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11548-013-0922-7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,7,18]],"date-time":"2019-07-18T10:06:34Z","timestamp":1563444394000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11548-013-0922-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,7,17]]},"references-count":41,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2014,3]]}},"alternative-id":["922"],"URL":"https:\/\/doi.org\/10.1007\/s11548-013-0922-7","relation":{},"ISSN":["1861-6410","1861-6429"],"issn-type":[{"value":"1861-6410","type":"print"},{"value":"1861-6429","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013,7,17]]}}}