[1]
Menze BH, Jakab A, Bauer S, et al. The multimodal brain tumor image segmentation benchmark (BRATS). IEEE Trans Med Imaging 2015; 34(10): 1993-2024.
[2]
Pereira S, Pinto A, Alves V, Silva CA. Brain tumor segmentation using convolutional neural networks in MRI images. IEEE Trans Med Imaging 2016; 35(5): 1240-51.
[3]
Sinha K, Sinha G. Efficient segmentation methods for tumor detection in MRI images. In: IEEE Students Conference on Electrical, Electronics and Computer Science 1-2 March 2014 Bhopal, India. 1-6.
[4]
Gordillo N, Montseny E, Sobrevilla P. State of the art survey on MRI brain tumor segmentation. Magn Reson Imaging 2013; 31(8): 1426-38.
[5]
Joseph RP, Singh CS, Manikandan M. Brain tumor MRI image segmentation and detection in image processing. Int J Res Eng Technol 2014; 3(1): 1-5.
[6]
Prajapati SJ, Jadhav KR. Brain tumor detection by various image segmentation techniques with introduction to non-negative matrix factorization. Brain 2015; 4(3): 600-3.
[7]
Thirumeni T, John R, Shaikh S. 3D segmentation of glioma from brain MR images using seeded region growing and fuzzy c-means clustering. Int J Res Eng Technol 2015; 4(12): 79-83.
[8]
Lakshmi A, Arivoli T. Brain tumor segmentation and its area calculation in brain Mr Images using k-mean clustering and fuzzy c-mean algorithm. In: IEEE-International Conference on Advances in Engineering, Science and Management (ICAESM -2012); 30-31 March 2012; Nagapattinam, Tamil Nadu, India; . 186-90.
[9]
Ortiz A, Gorriz J, Ramirez J, Salas-Gonzalez D. Improving MR brain image segmentation using self-organising maps and entropy-gradient clustering. Inf Sci 2014; 262: 117-36.
[10]
Zhang YD, Chen S, Wang SH, Yang JF, Phillips P. Magnetic resonance brain image classification based on weighted‐type fractional Fourier transform and nonparallel support vector machine. Int J Imaging Syst Technol 2015; 25(4): 317-27.
[11]
Praveen G, Agrawal A. Multi stage classification and segmentation of brain tumor. In: 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom) 16-18 March 2016; New Delhi, India;. 1628-32.
[12]
Hooda H, Verma OP, Singhal T. Brain tumor segmentation: A performance analysis using K-Means, Fuzzy C-Means and Region growing algorithms. In: International Conference on Advanced Communications, Control and Computing Technologies 8-10 May 2014; Ramanathapuram, India;. 1621-6.
[13]
Cabria I, Gondra I. MRI segmentation fusion for brain tumor detection. Inf Fusion 2017; 36: 1-9.
[14]
Sompong C, Wongthanavasu S. An efficient brain tumor segmentation based on cellular automata and improved tumor-cut algorithm. Expert Syst Appl 2017; 72: 231-44.
[15]
Subudhi BN, Thangaraj V, Sankaralingam E, Ghosh A. Tumor or abnormality identification from magnetic resonance images using statistical region fusion based segmentation. Magn Reson Imaging 2016; 34(9): 1292-304.
[16]
Pereira S, Pinto A, Oliveira J, Mendrik AM, Correia JH, Silva CA. Automatic brain tissue segmentation in MR images using Random Forests and Conditional Random Fields. J Neurosci Methods 2016; 270: 111-23.
[17]
Goetz M, Weber C, Binczyk F, et al. DALSA: Domain adaptation for supervised learning from sparsely annotated MR images. IEEE Trans Med Imaging 2016; 35(1): 184-96.
[18]
Ilunga-Mbuyamba E, Cruz-Duarte JM, Avina-Cervantes JG, Correa-Cely CR, Lindner D, Chalopin C. Active contours driven by Cuckoo Search strategy for brain tumour images segmentation. Expert Syst Appl 2016; 56: 59-68.
[19]
Vishnuvarthanan G, Rajasekaran MP, Subbaraj P, Vishnuvarthanan A. An unsupervised learning method with a clustering approach for tumor identification and tissue segmentation in magnetic resonance brain images. Appl Soft Comput 2016; 38: 190-212.
[20]
Verma H, Agrawal R, Sharan A. An improved intuitionistic fuzzy c-means clustering algorithm incorporating local information for brain image segmentation. Appl Soft Comput 2016; 46: 543-57.
[21]
Cordier N, Delingette H, Ayache N. A patch-based approach for the segmentation of pathologies: Application to glioma labelling. IEEE Trans Med Imaging 2016; 35(4): 1066-76.
[22]
Malathi R, Kamal N. Brain tumor detection and identification using K-means clustering technique. Int J Adv Network Appl (IJANA) 2015; 2015: 14-8.
[23]
Kumari A, Mehra R. Design of hybrid method PSO and SVM for detection of brain neoplasm. Int J Eng Adv Technol 2014; 3(4): 262-6.
[24]
Roy S, Bandyopadhyay SK. Detection and Quantification of Brain Tumor from MRI of Brain and it’s Symmetric Analysis. Int J Inform CommTechnol Res 2012; 2(6): 477-83.
[25]
Njeh I, Sallemi L, Ayed IB, et al. 3D multimodal MRI brain glioma tumor and edema segmentation: A graph cut distribution matching approach. Comput Med Imaging Graph 2015; 40: 108-19.
[26]
Moeskops P, Benders MJ, Chiţ SM, et al. Automatic segmentation of MR brain images of preterm infants using supervised classification. Neuroimage 2015; 118: 628-41.
[27]
Moreno JC, Prasath VS, Proenca H, Palaniappan K. Fast and globally convex multiphase active contours for brain MRI segmentation. Comput Vis Image Underst 2014; 125: 237-50.
[28]
Adhikari SK, Sing JK, Basu DK, Nasipuri M. Conditional spatial fuzzy C-means clustering algorithm for segmentation of MRI images. Appl Soft Comput 2015; 34: 758-69.
[29]
Demirhan A, Törü M, Güler I. Segmentation of tumor and edema along with healthy tissues of brain using wavelets and neural networks. IEEE J Biomed Health Inform 2015; 19(4): 1451-8.
[31]
Havaei M, Davy A, Warde-Farley D, et al. Brain tumor segmentation with deep neural networks. Med Image Anal 2017; 35: 18-31.
40
4
1