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Original Articles

Meningioma and peritumoral edema segmentation of preoperative MRI brain scans

, &
Pages 362-370 | Received 07 Mar 2016, Accepted 15 Oct 2016, Published online: 08 Nov 2016

References

  • Balafar M, Ramli A, Saripan M, Mashohor S. 2010. Review of brain MRI image segmentation methods. Artif Intell Rev. 33:261–274.10.1007/s10462-010-9155-0
  • Bauer S, Nolte LP, Reyes M. 2011. Fully automatic segmentation of brain tumor images using support vector machine classification in combination with hierarchical conditional random field regularization. In: Fichtinger G, Martel A, Peters T, editors. LNCS 6893 Proceedings of Med Image Comput Comput Assist Interv; 2011 September 18–22; Toronto. Berlin Heidelberg: Springer-Verlag.
  • Bauer S, Wiest R, Nolte L-P, Reyes M. 2013. A survey of MRI-based medical image analysis for brain tumor studies. Phys Med Biol. 58:R97–R129.10.1088/0031-9155/58/13/R97
  • Bezdek JC, Hall LO, Clarke LP. 1993. Review of MR image segmentation techniques using pattern recognition. Med Phys. 20:1033–1048.10.1118/1.597000
  • Binaghi E, Pedoia V, Balbi S. 2014. Collection and fuzzy estimation of truth labels in glial tumour segmentation studies. Comput Meth Biomech Biomed Eng Imaging Visual. 2:1–15.
  • Binaghi E, Omodei M, Pedoia V, Balbi S, Lattanzi D, Monti E. 2014. Automatic segmentation of MR brain tumor images using support vector machine in combination with Graph Cut. In: Madani K, Filipe J, editors. Proceedings of the International Conference on Neural Computation Theory and Applications; 2014 October 22–24; Rome: Scitepress.
  • Bouix S, Martin-Fernandez M, Ungar L, Koo MNMS, McCarley RW, Shenton ME. 2007. On evaluating brain tissue classifiers without a ground truth. NeuroImage. 36:1207–1224.10.1016/j.neuroimage.2007.04.031
  • Boykov Y, Funka-Lea G. 2006. Graph Cuts and efficient N-D image segmentation. Int J Comput Vision. 70:109–131.10.1007/s11263-006-7934-5
  • 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. 26:1124–1137.10.1109/TPAMI.2004.60
  • Boykov Y, Veksler O, Zabih R. 2001. Fast approximate energy minimization via graph cuts. IEEE Trans Pattern Anal Mach Intell. 23:1222–1239.10.1109/34.969114
  • Caroli M, Locatelli M, Prada F, Beretta F, Martinelli-Boneschi F, Campanella R, Arienta C. 2005. Surgery for intracranial meningiomas in the elderly: a clinical-radiological grading system as a predictor of outcome. J Neurosurg. 102:290–294.10.3171/jns.2005.102.2.0290
  • Chen V, Ruan S. 2010. Graph cut segmentation technique for MRI brain tumor extraction. In: Proceedings of 2nd International Conference on Image Processing Theory Tools and Applications; 2010 July 7–10; New York, NY. IEEE Press.
  • Chetverikov D, Svirko D, Stepanov D, Krsek P. 2002. The trimmed iterative closest point algorithm. In: Proceedings of 6th International Conference on Pattern recognition; 2002 August 11–15; Quebec. IEEE Press.
  • Clarke LP, Velthuizen R, Camacho M, Heine J, Vaidyanathan M, Hall L, Thatcher R, Silbiger MS. 1995. MRI segmentation: methods and applications. Magn Reson Imaging. 13(3):343–368.10.1016/0730-725X(94)00124-L
  • Despotović I, Goossens B, Philips W. 2015. MRI segmentation of the human brain: challenges, methods, and applications. Comput Math Methods Med. 2015, 23 p. Article ID 450341. doi:10.1155/2015/450341.
  • Duffau H. 2005. Lessons from brain mapping in surgery for low-grade glioma: insights into associations between tumour and brain plasticity. Lancet Neurol. 4:467–487.
  • Felzenszwalb PF, Huttenlocher DP. 2004. Efficient graph-based image segmentation. Int J Comput Vision. 59:167–181.10.1023/B:VISI.0000022288.19776.77
  • Gordillo N, Montseny E, Sobrevilla P. 2013. State of the art survey on MRI brain tumor segmentation. Magn Reson Imaging. 31:1426–1438.10.1016/j.mri.2013.05.002
  • Hamamci A, Kucuk N, Karaman K, Engin K, Unal G. 2012. Tumor-cut: segmentation of brain tumors on contrast enhanced MR images for radiosurgery applications. IEEE Trans Med Imaging. 31:790–804.10.1109/TMI.2011.2181857
  • Heckemann RA, Hajnal JV, Aljabar P, Rueckert D, Hammers A. 2006. Automatic anatomical brain MRI segmentation combining label propagation and decision fusion. NeuroImage. 33:115–126.10.1016/j.neuroimage.2006.05.061
  • Hsieh TM, Liu Y-M, Liao C-C, Xiao F, Chiang I-J, Wong J-M. 2011. Automatic segmentation of meningioma from non-contrasted brain MRI integrating fuzzy clustering and region growing. BMC Med Inf Decis Making. 11:343.10.1186/1472-6947-11-54
  • Kaus MR, Warfield SK, Nabavi A, Black PM, Jolesz FA, Kikinis R. 2001. Automated segmentation of MRI of brain tumors. Radiology. 218:586–591.10.1148/radiology.218.2.r01fe44586
  • MacQueen JB. 1967. Some methods for classification and analysis of multivariate observations. In: Proceedings of 5-th Berkeley Symposium on Mathematical Statistics and Probability; 1965 December 27–1966 January 7; Berkeley, CA. Berkeley, CA: University of California Press.
  • Pedoia V, Balbi S, Binaghi E. 2015. Fully automatic brain tumor segmentation by using competitive EM and Graph Cut. In: Murino V, Puppo E, editors. LNCS 9279 Proceedings of Int Conf on Image Analysis and Proc; 2015 September 7–11; Genoa. IEEE Press.
  • Pedoia V, Binaghi E. 2013. Automatic MRI 2D brain segmentation using graph searching technique. Num Meth Biomed Eng. 29:885–1013.
  • Santle KC, Govindan VK. 2012. A Review on graph based segmentation. Int J Image Graph Sign Process. 4:1–13.
  • Schoelkopf B, Smola A. 2002. Learning with kernels: support vector machines, regularization, optimization, and beyond. Cambridge: MIT Press.
  • Sacko O, Sesay M, Roux F-E, Riem F-E, Roux T, Grenier B, Liguoro D, Loiseau H. 2007. Intracranial meningioma surgery in the ninth decade of life. Neurosurgery. 61:950–955.10.1227/01.neu.0000303190.80049.7d
  • Suykens JAK, Van Gestel T, De Brabanter J, De Moor B, Vandewalle J. 2002. Least squares support vector machines. Singapore: World Scientific Publishing.10.1142/5089
  • Tuceryan M, Jain A. 1998. Texture analysis Inc. River Edge, NJ: World Scientific Publishing.
  • Toshiki E, Ayumi N, Hosam Shata MA, Kensuke M, Takashi W, Mika W, Hidefumi J, Hidenori E, Miki F, Yukihiko S, Teiji T. 2016. A study of prognostic factors in 45 cases of atypical meningioma. Acta Neurochir. 158:1661–1667.
  • Vapnik VN. 1995. The nature of statistical learning theory. New York, NY: Springer-Verlag.10.1007/978-1-4757-2440-0
  • Warfield SK, Zou KH, Wells WM. 2004. Simultaneous truth and performance level estimation (STAPLE): an algorithm for the validation of image segmentation. IEEE Trans Med Imaging. 23:903–921.10.1109/TMI.2004.828354
  • Withey D, Koles Z. 2008. A review of medical image segmentation: methods and available software. Int J Bioelectromagn. 10:125–148.

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