{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T14:33:00Z","timestamp":1767969180655,"version":"3.49.0"},"reference-count":63,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2016,12,26]],"date-time":"2016-12-26T00:00:00Z","timestamp":1482710400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Digit Imaging"],"published-print":{"date-parts":[[2017,6]]},"DOI":"10.1007\/s10278-016-9934-5","type":"journal-article","created":{"date-parts":[[2016,12,26]],"date-time":"2016-12-26T12:31:41Z","timestamp":1482755501000},"page":"376-390","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Liver Ultrasound Image Segmentation Using Region-Difference Filters"],"prefix":"10.1007","volume":"30","author":[{"given":"Nishant","family":"Jain","sequence":"first","affiliation":[]},{"given":"Vinod","family":"Kumar","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2016,12,26]]},"reference":[{"key":"9934_CR1","unstructured":"(September). Statistics and outlook for liver cancer. Available: http:\/\/www.cancerresearchuk.org\/about-cancer\/type\/liver-cancer\/treatment\/statistics-and-outlook-for-liver-cancer"},{"key":"9934_CR2","doi-asserted-by":"publisher","first-page":"3683","DOI":"10.1016\/j.asoc.2013.03.009","volume":"13","author":"W-L Lee","year":"2013","unstructured":"W.-L. Lee: An ensemble-based data fusion approach for characterizing ultrasonic liver tissue. Applied Soft Computing 13:3683\u20133692, 2013.","journal-title":"Applied Soft Computing"},{"key":"9934_CR3","doi-asserted-by":"publisher","first-page":"450","DOI":"10.1016\/j.eswa.2012.07.053","volume":"40","author":"JH Jeon","year":"2013","unstructured":"J. H. Jeon, J. Y. Choi, S. Lee, and Y. M. Ro: Multiple ROI selection based focal liver lesion classification in ultrasound images. Expert Systems with Applications 40:450\u2013457, 2013","journal-title":"Expert Systems with Applications"},{"key":"9934_CR4","doi-asserted-by":"publisher","first-page":"520","DOI":"10.1007\/s10278-014-9685-0","volume":"27","author":"J Virmani","year":"2014","unstructured":"J. Virmani, V. Kumar, N. Kalra, and N. Khandelwal: Neural network ensemble based CAD system for focal liver lesions from B-mode ultrasound. Journal of digital imaging 27:520\u2013537, 2014","journal-title":"Journal of digital imaging"},{"key":"9934_CR5","doi-asserted-by":"publisher","first-page":"382","DOI":"10.1109\/TMI.2003.809593","volume":"22","author":"W-L Lee","year":"2003","unstructured":"W.-L. Lee, Y.-C. Chen, and K.-S. Hsieh: Ultrasonic liver tissues classification by fractal feature vector based on M-band wavelet transform. IEEE Transactions on Medical Imaging 22:382\u2013392, 2003","journal-title":"IEEE Transactions on Medical Imaging"},{"key":"9934_CR6","doi-asserted-by":"publisher","first-page":"315","DOI":"10.1016\/j.compmedimag.2011.01.007","volume":"35","author":"D Mittal","year":"2011","unstructured":"D. Mittal, V. Kumar, S. C. Saxena, N. Khandelwal, and N. Kalra: Neural network based focal liver lesion diagnosis using ultrasound images Computerized Medical Imaging and Graphics 35:315\u2013323, 2011","journal-title":"Computerized Medical Imaging and Graphics"},{"key":"9934_CR7","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1016\/j.bspc.2014.09.013","volume":"16","author":"D Gupta","year":"2015","unstructured":"D. Gupta, R. Anand, and B. Tyagi: A hybrid segmentation method based on Gaussian kernel fuzzy clustering and region based active contour model for ultrasound medical images. Biomedical Signal Processing and Control 16:98\u2013112, 2015","journal-title":"Biomedical Signal Processing and Control"},{"key":"9934_CR8","doi-asserted-by":"publisher","unstructured":"J. Xu, K. Chen, X. Yang, D. Wu, and S. Zhu: Adaptive level set method for segmentation of liver tumors in minimally invasive surgery using ultrasound images. In: Bioinformatics and Biomedical Engineering, 2007. ICBBE 2007. The 1st International Conference on 1091\u20131094, 2007","DOI":"10.1109\/ICBBE.2007.282"},{"key":"9934_CR9","doi-asserted-by":"publisher","first-page":"177","DOI":"10.1016\/j.ins.2005.01.007","volume":"175","author":"W-L Lee","year":"2005","unstructured":"W.-L. Lee, Y.-C. Chen, Y.-C. Chen, and K.-S. Hsieh: Unsupervised segmentation of ultrasonic liver images by multiresolution fractal feature vector. Information Sciences 175:177\u2013199, 2005","journal-title":"Information Sciences"},{"key":"9934_CR10","doi-asserted-by":"publisher","unstructured":"M. Cvancarova, F. Albregtsen, K. Brabrand, and E. Samset: Segmentation of ultrasound images of liver tumors applying snake algorithms and GVF. In: International Congress Series 218\u2013223, 2005","DOI":"10.1016\/j.ics.2005.03.190"},{"key":"9934_CR11","doi-asserted-by":"publisher","first-page":"343","DOI":"10.1016\/0730-725X(94)00124-L","volume":"13","author":"L Clarke","year":"1995","unstructured":"L. Clarke, R. Velthuizen, M. Camacho, J. Heine, M. Vaidyanathan, L. Hall, et al.: MRI segmentation: methods and applications. Magnetic resonance imaging 13:343\u2013368, 1995","journal-title":"Magnetic resonance imaging"},{"key":"9934_CR12","doi-asserted-by":"publisher","first-page":"266","DOI":"10.1109\/83.902291","volume":"10","author":"TF Chan","year":"2001","unstructured":"T. F. Chan and L. Vese: Active contours without edges. IEEE transactions on Image processing 10:266\u2013277, 2001","journal-title":"IEEE transactions on Image processing"},{"key":"9934_CR13","unstructured":"C. Li, C. Xu, C. Gui, and M. D. Fox: Level set evolution without re-initialization: a new variational formulation. In: Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on 430\u2013436, 2005"},{"key":"9934_CR14","doi-asserted-by":"publisher","first-page":"1940","DOI":"10.1109\/TIP.2008.2002304","volume":"17","author":"C Li","year":"2008","unstructured":"C. Li, C.-Y. Kao, J. C. Gore, and Z. Ding: Minimization of region-scalable fitting energy for image segmentation. IEEE Transactions on Image processing 17:1940\u20131949, 2008","journal-title":"IEEE Transactions on Image processing"},{"key":"9934_CR15","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1023\/A:1007979827043","volume":"22","author":"V Caselles","year":"1997","unstructured":"V. Caselles, R. Kimmel, and G. Sapiro: Geodesic active contours. International journal of computer vision 22:61\u201379, 1997","journal-title":"International journal of computer vision"},{"key":"9934_CR16","doi-asserted-by":"publisher","unstructured":"C. Li, C.-Y. Kao, J. C. Gore, and Z. Ding: Implicit active contours driven by local binary fitting energy. In: Computer Vision and Pattern Recognition, 2007. CVPR'07. IEEE Conference on 1\u20137, 2007","DOI":"10.1109\/CVPR.2007.383014"},{"key":"9934_CR17","doi-asserted-by":"publisher","first-page":"1075","DOI":"10.1049\/iet-ipr.2012.0120","volume":"6","author":"J Yuan","year":"2012","unstructured":"J. Yuan: Active contour driven by region-scalable fitting and local Bhattacharyya distance energies for ultrasound image segmentation. IET Image Processing 6:1075\u20131083, 2012","journal-title":"IET Image Processing"},{"key":"9934_CR18","doi-asserted-by":"publisher","first-page":"252","DOI":"10.1049\/iet-ipr.2012.0461","volume":"7","author":"J Yuan","year":"2013","unstructured":"J. Yuan: Active contour driven by local divergence energies for ultrasound image segmentation. IET Image Processing 7:252\u2013259, 2013","journal-title":"IET Image Processing"},{"key":"9934_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10916-014-0068-3","volume":"38","author":"M Rastgarpour","year":"2014","unstructured":"M. Rastgarpour, J. Shanbehzadeh, and H. Soltanian-Zadeh: A hybrid method based on fuzzy clustering and local region-based level set for segmentation of inhomogeneous medical images. Journal of medical systems 38:1\u201315, 2014","journal-title":"Journal of medical systems"},{"key":"9934_CR20","doi-asserted-by":"publisher","first-page":"672","DOI":"10.1109\/72.159057","volume":"3","author":"LO Hall","year":"1992","unstructured":"L. O. Hall, A. M. Bensaid, L. P. Clarke, R. P. Velthuizen, M. S. Silbiger, and J. C. Bezdek: A comparison of neural network and fuzzy clustering techniques in segmenting magnetic resonance images of the brain, IEEE Transactions on Neural Networks 3:672\u2013682, 1992","journal-title":"IEEE Transactions on Neural Networks"},{"key":"9934_CR21","doi-asserted-by":"publisher","first-page":"300","DOI":"10.1016\/j.acra.2007.10.012","volume":"15","author":"Z Lao","year":"2008","unstructured":"Z. Lao, D. Shen, D. Liu, A. F. Jawad, E. R. Melhem, L. J. Launer, et al.: Computer-assisted segmentation of white matter lesions in 3D MR images using support vector machine. Academic radiology 15:300\u2013313, 2008","journal-title":"Academic radiology"},{"key":"9934_CR22","doi-asserted-by":"publisher","unstructured":"S. Ruan, S. Lebonvallet, A. Merabet, and J.-M. Constans: Tumor segmentation from a multispectral MRI images by using support vector machine classification. In: Biomedical Imaging: From Nano to Macro, 2007. ISBI 2007. 4th IEEE International Symposium on 1236\u20131239, 2007","DOI":"10.1109\/ISBI.2007.357082"},{"key":"9934_CR23","doi-asserted-by":"publisher","first-page":"2127","DOI":"10.1109\/TMI.2013.2274734","volume":"32","author":"P Karasev","year":"2013","unstructured":"P. Karasev, I. Kolesov, K. Fritscher, P. Vela, P. Mitchell, and A. Tannenbaum: Interactive medical image segmentation using PDE control of active contours. IEEE Transactions on Medical Imaging 32:2127\u20132139, 2013","journal-title":"IEEE Transactions on Medical Imaging"},{"key":"9934_CR24","doi-asserted-by":"publisher","first-page":"1147","DOI":"10.1016\/j.cviu.2013.04.008","volume":"117","author":"A Kasaiezadeh","year":"2013","unstructured":"A. Kasaiezadeh and A. Khajepour: Multi-agent stochastic level set method in image segmentation. Computer Vision and Image Understanding 117:1147\u20131162, 2013","journal-title":"Computer Vision and Image Understanding"},{"key":"9934_CR25","doi-asserted-by":"publisher","first-page":"2007","DOI":"10.1109\/TIP.2011.2146190","volume":"20","author":"C Li","year":"2011","unstructured":"C. Li, R. Huang, Z. Ding, J. C. Gatenby, D. N. Metaxas, and J. C. Gore: A level set method for image segmentation in the presence of intensity inhomogeneities with application to MRI. IEEE Transactions on Image Processing 20:2007\u20132016, 2011","journal-title":"IEEE Transactions on Image Processing"},{"key":"9934_CR26","doi-asserted-by":"publisher","first-page":"1577","DOI":"10.1109\/TUFFC.2011.1985","volume":"58","author":"CY Ahn","year":"2011","unstructured":"C. Y. Ahn, Y. M. Jung, O. I. Kwon, and J. K. Seo: A regularization technique for closed contour segmentation in ultrasound images. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control 58:1577\u20131589, 2011","journal-title":"IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control"},{"key":"9934_CR27","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1007\/BF00133570","volume":"1","author":"M Kass","year":"1988","unstructured":"M. Kass, A. Witkin, and D. Terzopoulos: Snakes: Active contour models. International journal of computer vision 1:321\u2013331, 1988","journal-title":"International journal of computer vision"},{"key":"9934_CR28","doi-asserted-by":"publisher","first-page":"383","DOI":"10.1049\/iet-ipr.2013.0020","volume":"8","author":"X Wang","year":"2014","unstructured":"X. Wang, W. Zhang, and Q. Ji: Image object extraction with shape and edge-driven Markov random field model. IET Image Processing 8:383\u2013396, 2014","journal-title":"IET Image Processing"},{"key":"9934_CR29","doi-asserted-by":"publisher","first-page":"3087","DOI":"10.1109\/TIP.2013.2259833","volume":"22","author":"A Ghosh","year":"2013","unstructured":"A. Ghosh, B. N. Subudhi, and L. Bruzzone: Integration of Gibbs Markov random field and Hopfield-type neural networks for unsupervised change detection in remotely sensed multitemporal images. IEEE Transactions on Image Processing 22:3087\u20133096, 2013","journal-title":"IEEE Transactions on Image Processing"},{"key":"9934_CR30","unstructured":"Q. Wang: HMRF-EM-image: implementation of the hidden Markov random field model and its expectation-maximization algorithm. arXiv preprint arXiv:1207.3510, 2012"},{"key":"9934_CR31","unstructured":"X. Huang, J. Dong, and M. Wang: Paper web defection segmentation using Gauss-Markov random field texture features. In: Image Analysis and Signal Processing (IASP), 2011 International Conference on 167\u2013170, 2011"},{"key":"9934_CR32","doi-asserted-by":"publisher","unstructured":"J. Lai, J. J. Ford, P. O'Shea, and R. Walker: Hidden Markov model filter banks for dim target detection from image sequences. In: Digital Image Computing: Techniques and Applications (DICTA) 312\u2013319, 2008","DOI":"10.1109\/DICTA.2008.61"},{"key":"9934_CR33","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1109\/TIP.2006.884933","volume":"16","author":"J Wu","year":"2007","unstructured":"J. Wu and A. Chung: A segmentation model using compound Markov random fields based on a boundary model. IEEE Transactions on Image Processing 16:241\u2013252, 2007","journal-title":"IEEE Transactions on Image Processing"},{"key":"9934_CR34","doi-asserted-by":"publisher","first-page":"505","DOI":"10.1109\/TAC.2005.844896","volume":"50","author":"L Xie","year":"2005","unstructured":"L. Xie, V. Ugrinovskii, and I. R. Petersen: Probabilistic distances between finite-state finite-alphabet hidden Markov models. IEEE Transactions on, Automatic Control 50:505\u2013511, 2005","journal-title":"IEEE Transactions on, Automatic Control"},{"key":"9934_CR35","doi-asserted-by":"publisher","first-page":"1380","DOI":"10.1109\/TPAMI.2003.1240112","volume":"25","author":"JL Marroquin","year":"2003","unstructured":"J. L. Marroquin, E. A. Santana, and S. Botello: Hidden Markov measure field models for image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence 25:1380\u20131387, 2003","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"9934_CR36","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1109\/42.981233","volume":"21","author":"G Xiao","year":"2002","unstructured":"G. Xiao, M. Brady, J. A. Noble, and Y. Zhang: Segmentation of ultrasound B-mode images with intensity inhomogeneity correction. IEEE Transactions on Medical Imaging 21:48\u201357, 2002","journal-title":"IEEE Transactions on Medical Imaging"},{"key":"9934_CR37","doi-asserted-by":"publisher","first-page":"954","DOI":"10.1109\/83.772239","volume":"8","author":"X Descombes","year":"1999","unstructured":"X. Descombes, R. D. Morris, J. Zerubia, and M. Berthod: Estimation of Markov random field prior parameters using Markov chain Monte Carlo maximum likelihood. IEEE Transactions on Image Processing 8:954\u2013963, 1999","journal-title":"IEEE Transactions on Image Processing"},{"key":"9934_CR38","doi-asserted-by":"publisher","first-page":"906","DOI":"10.1109\/TMI.2009.2012888","volume":"28","author":"X Liu","year":"2009","unstructured":"X. Liu, D. L. Langer, M. Haider, Y. Yang, M. N. Wernick, and \u0130. \u015e. Yetik: Prostate cancer segmentation with simultaneous estimation of Markov random field parameters and class. IEEE Transactions on Medical Imaging 28:906\u2013915, 2009","journal-title":"IEEE Transactions on Medical Imaging"},{"key":"9934_CR39","doi-asserted-by":"publisher","first-page":"402","DOI":"10.1109\/TPAMI.2004.1262337","volume":"26","author":"N Paragios","year":"2004","unstructured":"N. Paragios, O. Mellina-Gottardo, and V. Ramesh: Gradient vector flow fast geometric active contours. IEEE Transactions on Pattern Analysis and Machine Intelligence 26:402\u2013407, 2004","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"9934_CR40","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1023\/A:1014080923068","volume":"46","author":"N Paragios","year":"2002","unstructured":"N. Paragios and R. Deriche: Geodesic active regions and level set methods for supervised texture segmentation. International Journal of Computer Vision 46:223\u2013247, 2002","journal-title":"International Journal of Computer Vision"},{"key":"9934_CR41","doi-asserted-by":"publisher","first-page":"939","DOI":"10.1109\/34.464559","volume":"17","author":"DK Panjwani","year":"1995","unstructured":"D. K. Panjwani and G. Healey: Markov random field models for unsupervised segmentation of textured color images. IEEE Transactions on Pattern Analysis and Machine Intelligence 17:939\u2013954, 1995","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"9934_CR42","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1006\/gmip.1997.0431","volume":"59","author":"F Salzenstein","year":"1997","unstructured":"F. Salzenstein and W. Pieczynski: Parameter estimation in hidden fuzzy Markov random fields and image segmentation. Graphical models and image processing 59:205\u2013220, 1997","journal-title":"Graphical models and image processing"},{"key":"9934_CR43","doi-asserted-by":"publisher","first-page":"825","DOI":"10.1016\/j.patcog.2006.07.011","volume":"40","author":"W Cai","year":"2007","unstructured":"W. Cai, S. Chen, and D. Zhang: Fast and robust fuzzy c-means clustering algorithms incorporating local information for image segmentation. Pattern Recognition 40:825\u2013838, 2007","journal-title":"Pattern Recognition"},{"key":"9934_CR44","doi-asserted-by":"publisher","first-page":"994","DOI":"10.1016\/j.mri.2009.01.024","volume":"27","author":"K Sikka","year":"2009","unstructured":"K. Sikka, N. Sinha, P. K. Singh, and A. K. Mishra: A fully automated algorithm under modified FCM framework for improved brain MR image segmentation. Magnetic Resonance Imaging 27:994\u20131004, 2009","journal-title":"Magnetic Resonance Imaging"},{"key":"9934_CR45","doi-asserted-by":"publisher","first-page":"1351","DOI":"10.1109\/TFUZZ.2008.2005008","volume":"16","author":"SP Chatzis","year":"2008","unstructured":"S. P. Chatzis and T. Varvarigou: A fuzzy clustering approach toward hidden Markov random field models for enhanced spatially constrained image segmentation. IEEE Transactions on Fuzzy Systems 16:1351\u20131361, 2008","journal-title":"IEEE Transactions on Fuzzy Systems"},{"key":"9934_CR46","doi-asserted-by":"publisher","unstructured":"M. A. Jaffar, N. Naveed, B. Ahmed, A. Hussain, and A. M. Mirza: Fuzzy C-means clustering with spatial information for color image segmentation. In: Electrical Engineering, 2009. ICEE'09. Third International Conference on, 2009, pp. 1\u20136.","DOI":"10.1109\/ICEE.2009.5173186"},{"key":"9934_CR47","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1016\/j.compmedimag.2005.10.001","volume":"30","author":"K-S Chuang","year":"2006","unstructured":"K.-S. Chuang, H.-L. Tzeng, S. Chen, J. Wu, and T.-J. Chen: Fuzzy c-means clustering with spatial information for image segmentation. Computerized medical imaging and graphics 30:9\u201315, 2006","journal-title":"Computerized medical imaging and graphics"},{"key":"9934_CR48","doi-asserted-by":"publisher","first-page":"1548","DOI":"10.1016\/j.patrec.2007.03.012","volume":"28","author":"Y Xia","year":"2007","unstructured":"Y. Xia, T. Wang, R. Zhao, and Y. Zhang: Image segmentation by clustering of spatial patterns. Pattern Recognition Letters 28:1548\u20131555, 2007","journal-title":"Pattern Recognition Letters"},{"key":"9934_CR49","doi-asserted-by":"publisher","first-page":"327","DOI":"10.1016\/j.bspc.2008.06.003","volume":"3","author":"L He","year":"2008","unstructured":"L. He and I. R. Greenshields: An MRF spatial fuzzy clustering method for fMRI SPMs. Biomedical Signal Processing and Control 3:327\u2013333, 2008","journal-title":"Biomedical Signal Processing and Control"},{"key":"9934_CR50","doi-asserted-by":"publisher","first-page":"685","DOI":"10.1016\/j.compmedimag.2008.08.004","volume":"32","author":"J Wang","year":"2008","unstructured":"J. Wang, J. Kong, Y. Lu, M. Qi, and B. Zhang: A modified FCM algorithm for MRI brain image segmentation using both local and non-local spatial constraints. Computerized medical imaging and graphics 32:685\u2013698, 2008","journal-title":"Computerized medical imaging and graphics"},{"key":"9934_CR51","doi-asserted-by":"publisher","first-page":"1907","DOI":"10.1109\/TSMCB.2004.831165","volume":"34","author":"S Chen","year":"2004","unstructured":"S. Chen and D. Zhang: Robust image segmentation using FCM with spatial constraints based on new kernel-induced distance measure. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 34:1907\u20131916, 2004","journal-title":"IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics"},{"key":"9934_CR52","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1016\/j.artmed.2004.01.012","volume":"32","author":"D-Q Zhang","year":"2004","unstructured":"D.-Q. Zhang and S.-C. Chen: A novel kernelized fuzzy c-means algorithm with application in medical image segmentation. artificial intelligence in medicine 32:37\u201350, 2004","journal-title":"artificial intelligence in medicine"},{"key":"9934_CR53","doi-asserted-by":"publisher","first-page":"607","DOI":"10.1016\/j.patcog.2004.09.006","volume":"38","author":"D-W Kim","year":"2005","unstructured":"D.-W. Kim, K. Y. Lee, D. Lee, and K. H. Lee: Evaluation of the performance of clustering algorithms in kernel-induced feature space. Pattern Recognition 38:607\u2013611, 2005","journal-title":"Pattern Recognition"},{"key":"9934_CR54","doi-asserted-by":"publisher","first-page":"1713","DOI":"10.1016\/j.patrec.2008.04.016","volume":"29","author":"M-S Yang","year":"2008","unstructured":"M.-S. Yang and H.-S. Tsai: A Gaussian kernel-based fuzzy c-means algorithm with a spatial bias correction. Pattern recognition letters 29:1713\u20131725, 2008","journal-title":"Pattern recognition letters"},{"key":"9934_CR55","doi-asserted-by":"publisher","unstructured":"J. Kawa and E. Pietka: Kernelized fuzzy c-means method in fast segmentation of demyelination plaques in multiple sclerosis. In: Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE 5616\u20135619, 2007","DOI":"10.1109\/IEMBS.2007.4353620"},{"key":"9934_CR56","doi-asserted-by":"publisher","first-page":"1580","DOI":"10.1016\/j.patrec.2008.03.012","volume":"29","author":"L Liao","year":"2008","unstructured":"L. Liao, T. Lin, and B. Li: MRI brain image segmentation and bias field correction based on fast spatially constrained kernel clustering approach. Pattern Recognition Letters 29:1580\u20131588, 2008","journal-title":"Pattern Recognition Letters"},{"key":"9934_CR57","doi-asserted-by":"publisher","first-page":"1445","DOI":"10.1049\/el:20073093","volume":"43","author":"D Graves","year":"2007","unstructured":"D. Graves and W. Pedrycz: Performance of kernel-based fuzzy clustering. Electronics Letters 43:1445\u20131446, 2007","journal-title":"Electronics Letters"},{"key":"9934_CR58","doi-asserted-by":"publisher","first-page":"145","DOI":"10.1109\/TASSP.1984.1164279","volume":"32","author":"J Bednar","year":"1984","unstructured":"J. Bednar and T. Watt: Alpha-trimmed means and their relationship to median filters. IEEE Transactions on Acoustics, Speech, and Signal Processing 32:145\u2013153, 1984","journal-title":"IEEE Transactions on Acoustics, Speech, and Signal Processing"},{"key":"9934_CR59","doi-asserted-by":"publisher","first-page":"1326","DOI":"10.1109\/29.1660","volume":"36","author":"A Restrepo","year":"1988","unstructured":"A. Restrepo and A. C. Bovik: Adaptive trimmed mean filters for image restoration. IEEE Transactions on Acoustics, Speech, and Signal Processing 36:1326\u20131337, 1988","journal-title":"IEEE Transactions on Acoustics, Speech, and Signal Processing"},{"key":"9934_CR60","doi-asserted-by":"crossref","unstructured":"Y. B. Rytsar and I. B. Ivasenko: Application of (alpha,beta)-trimmed mean filtering for removal of additive noise from images 45\u201352, 1997","DOI":"10.1117\/12.284817"},{"key":"9934_CR61","doi-asserted-by":"publisher","first-page":"627","DOI":"10.1109\/TIP.2003.821115","volume":"13","author":"R Oten","year":"2004","unstructured":"R. Oten and R. J. P. d. Figueiredo: Adaptive alpha-trimmed mean filters under deviations from assumed noise model. IEEE Transactions on Image Processing 13:627\u2013639, 2004","journal-title":"IEEE Transactions on Image Processing"},{"key":"9934_CR62","doi-asserted-by":"publisher","first-page":"869","DOI":"10.1109\/34.161346","volume":"14","author":"L Lam","year":"1992","unstructured":"L. Lam, S.-W. Lee, and C. Y. Suen: Thinning Methodologies\u2014A Comprehensive Survey. IEEE Trans. Pattern Anal. Mach. Intell. 14:869\u2013885, 1992","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"9934_CR63","unstructured":"(18 January). bwmorph. Available: https:\/\/in.mathworks.com\/help\/images\/ref\/bwmorph.html"}],"container-title":["Journal of Digital Imaging"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10278-016-9934-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10278-016-9934-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10278-016-9934-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,16]],"date-time":"2019-09-16T19:47:16Z","timestamp":1568663236000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10278-016-9934-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,12,26]]},"references-count":63,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2017,6]]}},"alternative-id":["9934"],"URL":"https:\/\/doi.org\/10.1007\/s10278-016-9934-5","relation":{},"ISSN":["0897-1889","1618-727X"],"issn-type":[{"value":"0897-1889","type":"print"},{"value":"1618-727X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,12,26]]}}}