Methods on Skull Stripping of MRI Head Scan Images—a Review
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Haacke EM, Brown RW, Thompson MR, Venkatesan R: Magnetic resonance imaging, physical principles and sequence design. John Willey & Sons, New York, 1999
Quencer RM, Bradley WG: MR imaging of the brain: what constitutes the minimum acceptable capability? Am J Neuroradiol 22(8):1449–1450, 2001
Cheour M: Advantages of brain MRI, 2010, Available at: RadiologyInfo.org
Schmid P: Segmentation of digitized dermatoscopic images by Two-dimensional colour clustering. IEEE Trans Med Imaging 18(2):164–171, 1999
NLM-National Library of Medicine, (Rockville Pike, Bethesda U.S., 2011), Available online at: http://www.nlm.nih.gov
Gonzalez RC, Woods RE: Digital image processing, 3rd edition. Prentice Hall of India (P) Ltd, New Delhi, 2008
Pham DL, Xu C, Prince JL: Current methods in medical image segmentation. Annu Rev Biomed Eng 2(1):315–338, 2000
Hizukuri A, Nakayama R, Nakako N, Kawanaka H, Takase H, Yamamoto K, Tsuruoka S: Computerized segmentation method for individual calcifications within clustered microcalcifications while maintaining their shapes on magnification mammograms. J Digit Imaging 25:377–386, 2012
Younis A, Ibrahim M, Kabuka M, John N: An artificial immune-activated neural network applied to brain 3D MRI segmentation. J Digit Imaging 21(1):69–88, 2008
Erickson BJ, Avula RTV: An algorithm for automatic segmentation and classification of magnetic resonance brain images. J Digit Imaging 11(2):74–82, 1998
Handels H, Tolxdorff T: A new segmentation algorithm for knowledge acquisition in tissue- characterizing magnetic resonance imaging. J Digit Imaging 3(2):89–94, 1990
Hogan RE, Mark KE, Choudhuri I, Wang L, Joshi S, Miller MI, Bucholz RD: Magnetic resonance imaging deformation-based segmentation of the hippocampus in patients with mesial temporal sclerosis and temporal lobe epilepsy. J Digit Imaging 13(1):217–218, 2000
Fennema-Notestine C, Ozyurt IB, Clark CP, Morris S, Bischoff-Grethe A, Bondi MW, Jernigan TL, Fischl B, Segonne F, Shattuck DW, Leahy RM, Rex DE, Toga AW, Zou KH, Brain M, Brown GG: Quantitative evaluation of automated skull-stripping methods applied to contemporary and legacy images: effects of diagnosis, bias correction and slice location. Hum Brain Mapp 27(2):99–113, 2006
Matsumoto S, Asato R, Konishi J: A fast Way to visualize the brain surface with volume rendering of MRI data. J Digit Imaging 12(4):185–190, 1999
Mahmood Q, Chodorowski A, Mehnert A, Gellermann J, Persson M, Unsupervised segmentation of head tissues from multi-modal MR images for EEG source localization J Digit Imaging, 2014
Hata Y, Kobashi S, Kondo K, Kitamura YT, Yanagida T: Transcranial ultrasonography system for visualizing skull and brain surface aided by fuzzy expert system. IEEE Trans Syst Man Cybern 35(6):1360–1373, 2005
Klein A, Ghosh SS, Avants B, Yeo B, Fischl B, Ardekani B, Gee JC, Mann J, Parsey RV: Evaluation of volume-based and surface-based brain image registration methods. NeuroImage 51(1):214–220, 2010
Kalkers NF, Ameziane N, Bot JC, Minneboo A, Polman CH, Barkhof F: Longitudinal brain volume measurement in multiple sclerosis: rate of brain atrophy is independent of the disease subtype. Archit Neurol 58(10):1572–1576, 2002
Wels M, Zheng Y, Huber M, Hornegger J, Comaniciu D: A discriminative model-constrained EM approach to 3D MRI brain tissue classification and intensity Non-uniformity correction. Phys Med Biol 56(11):3269–3300, 2011
Wang L, Chen Y, Pan X, Hong X, Xia D: Level set segmentation of brain magnetic resonance images based on local gaussian distribution fitting energy. J Neurosci Methods 188(2):316–325, 2010
Thompson PM, Mega MS, Woods RP, Zoumalan CI, Lindshield CJ, Blanton RE, Moussai J, Holmes CJ, Cummings JL, Toga AW: Cortical change in Alzheimer’s disease detected with a disease-specific population-based brain atlas. Cereb Cortex 11(1):1–16, 2001
Tosun D, Rettmann ME, Naiman DQ, Resnick SM, Kraut MA, Prince JL: Cortical reconstruction using implicit surface evolution: accuracy and precision analysis. NeuroImage 29(3):838–852, 2006
MacDonald D, Kabani N, Avis D, Evans AC: Automated 3-D extraction of inner and outer surfaces of cerebral cortex from MRI. NeuroImage 12(3):340–356, 2000
Zhao L, Ruotsalainen U, Hirvonen J, Hietala J, Tohka J: Automatic cerebral and cerebellar hemisphere segmentation in 3D MRI: adaptive disconnection algorithm. Med Image Anal 14(3):360–372, 2010
Zivadinov R, Bagnato F, Nasuelli D, Bastianello S, Bratina A, Locatelli L, Watts K, Finamore L, Grop A, Dwyer M, Catalan M, Clemenzi A, Millefiorini E, Bakshi R, Zorzon M: Short-term brain atrophy changes in relapsing-remitting multiple sclerosis. Neurol Sci 223(2):185–193, 2004
Rusinek H, de Leon MJ, George AE, Stylopoulos LA, Chandra R, Smith G, Rand T, Mourino M, Kowalski H: Alzheimer disease: measuring loss of cerebral gray matter with MR imaging. Radiology 178(1):109–114, 1991
Tanskanen P, Veijola JM, Piippo UK, Haapea M, Miettunen JA, Pyhtinen J, Bullmore ET, Jones PB, Isohanni MK: Hippocampus and amygdala volumes in schizophrenia and other psychoses in the northern Finland 1966 birth cohort. Schizophr Res 75(2-3):283–294, 2005
Blanton RE, Levitt JG, Peterson JR, Fadale D, Sporty ML, Lee M, To D, Mormino EC, Thompson PM, McCracken JT, Toga AW: Gender differences in the left inferior frontal gyrus in normal children. NeuroImage 22(2):626–636, 2004
Brummer ME, Mersereau RM, Eisner RL, Lewine RRJ, Caeslles V, Kimmel R, Sapiro G: Automatic detection of brain contours in MRI datasets. IEEE Trans Image Process 12(2):153–166, 1993
Zhuang AH, Valentino DJ, Toga AW: Skull stripping magnetic resonance images using a model-based level sets. NeuroImage 32(1):79–92, 2006
Tsai C, Manjunath BS, Jagadeesan R: Automated segmentation of brain MR images. Pattern Recogn 28(12):1825–1837, 1995
Sandor S, Leahy RM: Surface-based labeling of cortical anatomy using a deformable atlas. IEEE Trans Med Imaging 16(1):41–54, 1997
Lemieux G, Krakow KH, Woermann FG: Fast, automatic segmentation of the brain in T1-weighted volume magnetic resonance image data. Proc SPIE Med Imaging: Image Processing 3661:152–160, 1999
Shattuck DW, Sandor-Leahy SR, Schaper KA, Rottenberg DA, Leahy RM: Magnetic resonance image tissue classification using a partial volume model. NeuroImage 13(5):856–876, 2001
Shanthi KJ, Sasikumar M: Skull stripping and automatic segmentation of brain MRI using seed growth and threshold techniques, Proc. International Conference on Intelligent and Advanced Systems, Kuala Lumpur 1:422-426,2007
Mikheev B, Nevsky G, Govindan S, Grossman R, Rusinek H: Fully automatic segmentation of the brain from T1-weighted MRI using bridge burner algorithm. J Magn Reson Imaging 27(6):1235–1241, 2008
Park GJ, Lee C: Skull stripping based on region growing for magnetic resonance images. NeuroImage 47(4):1394–1407, 2009
Gao J, Xie M: Skull stripping MR brain images using anisotropic diffusion filtering and morphological processing, Proc. International Symposium on Computer Network and Multimedia Technology, Wuhan 1:1-4,2009
Somasundaram K, Kalavathi P: Automatic skull stripping of magnetic resonance images (MRI) of human head scans using image contour. Image Processing, Allied Publisher, New Delhi, 2010, pp 147–151
Somasundaram K, Kalavathi P: A hybrid method for automatic skull stripping of magnetic resonance images (MRI) of human head scans. Proc. International Conference on Computing Communication and Networking Technologies (ICCCNT), Karur, Tamilnadu, 1-5, 2010
Somasundaram K, Kalaiselvi T: Fully automatic brain extraction algorithm for axial T2- weighted magnetic resonance images. Comput Biol Med 40(10):811–822, 2010
Somasundaram K, Kalaiselvi T: Automatic brain extraction methods for T1 magnetic resonance images using region labeling and morphological operations. Comput Biol Med 41(8):2011
Carass A, Cuzzocreo J, Wheeler MB, Bazin PL, Resnick SM, Prince JL: Simple paradigm for extra-cerebral tissue removal: algorithm and analysis. NeuroImage 56(4):1982–1992, 2011
Cox RW: AFNI: software for analysis and visualization of functional magnetic resonance Neuroimages. Comput Biomed Res 29(3):162–173, 1996
Ward BD: 3dIntracranial: automatic segmentation of intracranial region. Technical Report, Biophysics Research Institute, Medical College of Wisconsin, UK, 1999
Huh S, Ketter TA, John KH, Lee C: Automated cerebrum segmentation from three- dimensional sagittal brain MR images. Comput Biol Med 32(5):311–328, 2002
Dawant BM, Hartmann SL, Thirion JP, Maes F, Vandermeulen D, Demaerel P: Automatic 3-D segmentation of internal structures of the head in MR images using a combination of similarity and free-form transformations: part I. Methodology and validation on normal subjects. IEEE Trans Med Imaging 18(10):909–916, 1999
Pham DL, Prince JL: Adaptive fuzzy segmentation of magnetic resonance images. IEEE Trans Med Imaging 18(9):737–752, 1999
Hahn HK, Peitgen HO: The Skull Stripping Problem in MRI Solved by Single 3D Watershed Transform, Proc. Medical Image Computing and Computer Assisted Intervention (MICCAI). LNCS 2000:134–143, 1935
Grau V, Mewes AUJ, Alcaiz M, Kikinis R, Warfield SK: Improved watershed transform for medical image segmentation using prior information. IEEE Trans Med Imaging 23(4):447–458, 2004
Zu YS, Guang HY, Jing ZL: Automated histogram-based brain segmentation in T1- weighted three-dimensional magnetic resonance head images. NeuroImage 17(3):1587–1598, 2002
Sadananthan S, Zheng W, Chee M, Zagorodnov V: Skull stripping using graph cuts. NeuroImage 49(1):225–239, 2010
Somasundaram K, Kalavathi P: Skull stripping of MRI head scans based on 2D region growing, Proc. ICOM11 Tiruchirappalli, Tamil Nadu, 2011, pp 18–23
Somasundaram K, Kalavathi P: Brain segmentation in magnetic resonance human head scans using multi-seeded region growing. Imaging Sci J 62(5):273–284, 2014
Kalavathi P: Computation of brain asymmetry in 2D brain images. Int J Sci Eng Res 5(7):1167–1171, 2014
Aboutanos GB, Nikanne J, Watkins N, Dawant BM: Model creation and deformation for the automatic segmentation of the brain in MR images. IEEE Trans Biomed Eng 46(11):1346–1356, 1999
Zeng X, Staib LH, Schultz RT, Duncan JS: Segmentation and measurement of the cortex from 3-D MR images using coupled-surfaces propagation. IEEE Trans Med Imaging 18(10):927–937, 1999
Suri JS: Two-dimensional fast magnetic resonance brain segmentation. IEEE Eng Med Biol 20(4):84–95, 2001
Baillard C, Hellier P, Barillot C: Segmentation of brain 3D MR images using level sets and dense registration. Med Image Anal 5(3):185–194, 2001
Atkins MS, Siu K, Law B, Orchard JJ, Rosenbaum WL: Difficulties of T1 brain MRI segmentation techniques, medical imaging. Proc. SPIE 4684(1):1837–1844, 2001
Jenkinson M, Pechaud M, Smith S: BET2 - MR-based estimation of brain, skull and scalp surfaces. Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Oxford, 2005
3dSkullStrip, a part of the AFNI (Analysis of Functional Neuro Images) package. available at http://afni.nimh.nih.gov
Lao Z, Shen D, Davatzikas C: Statistical shape model for automatic skull-stripping of brain images. Proc. IEEE International Symposium on Biomedical Imaging, Washington, D.C, 2002, pp 855–858
John C, Kevin W, Emma L, Chao C, Barbara P, Declan J: Statistical morphological skull stripping of adult and infant MRI data. Comput Biol Med 37(3):342–357, 2007
Yunjie C, Jianwei Z, Shunfeng W: A new fast brain skull stripping method, biomedical engineering and informatics. Proc. 2nd International Conference on Biomedical Engineering and Informatics, BMEI09, Tianjin, 2009
Liu JX, Chen YS, Chen LF: Accurate and robust extraction of brain regions using a deformable model based on radial basis functions. J Neurosci Methods 183(2):255–266, 2009
Merisaari H, Parkkola R, Alhoniemia E, Teras M, Lehtonend L, Haataja L, Lapinleimu H, Nevalainen OS: Gaussian mixture model-based segmentation of MR images taken from premature infant brains. J Neurosci Methods 182(1):110–122, 2009
Tao X, Chang MC: A skull stripping method using deformable surface and tissue classification, medical imaging. Proc. SPIE 7:623–630, 2010
Somasundaram K, Kalavathi P: Skull stripping of MRI head scans based on chan-vese active contour model. Int J Knowl Manag e-learning 3(1):7–14, 2011
Hwang J, Han Y, Park H: Skull-stripping method for brain MRI using a 3D level Set with a speedup operator. J Magn Reson Imaging 34(2):445–456, 2011
Zhang H, Liu J, Zhu Z, et al: An automated and dimple method for brain MR image extraction, BioMed Eng OnLine 10(81),2011
Somasundaram K, Kalavathi P: A novel skull stripping technique for T1-weighted MRI human head Scans, Proc. ICVGIP 1-8,2012
Galdames FJ, Jaillet F, Perez CA: An accurate skull stripping method based on simplex meshes and histogram analysis in magnetic resonance images. J Neurosci Methods 206(2):109–113, 2012
Somasundaram K, Kalavathi P: Contour-based brain segmentation method for magnetic resonance imaging human head scans. J Comput Assist Tomogr 37(3):353–368, 2013
Dale AM, Fischl B, Sereno MI: Cortical surface-based analysis I: segmentation and surface reconstruction. NeuroImage 9(2):179–194, 1999
Wang Y, Nie J, Yap P-T, Shi F, Guo L, Shen D: Robust deformable-surface-based skull- stripping for large-scale studies, Proc. medical image computing and computer assisted intervention (MICCAI). LNCS 6893:635–642, 2011
Kobashi S, Moto FY, Ogawa MD, Ando K, Ishikura R, Kando SH, Katy Y: Fuzzy- ASM based automated skull stripping method from infantile brain MR images. Proc. IEEE Int Conf Granular Comput San Jose California 1:632–635, 2007
Mahapatra D: Skull stripping of neonatal brain MRI: using prior shape information with graph cuts. J Digit Imaging 25(6):802–814, 2012
Leung KK, Barnes J, Modat M, Ridgway GR, Bartlett JW, Fox NC, Ourselin S: Brain MAPS: an automated, accurate and robust brain extraction technique using a template library. NeuroImage 55(3):1091–1108, 2011
Eskildsen SF, Coupe P, Fonov V, Manjon JV, Leung KK, Guizard N, Wassef SN, Ostergaard LR, Collins DL: BEaST: brain extraction based on Non-local segmentation technique. NeuroImage 59(3):2362–2373, 2012
Kapur T, Grimson WEL, Wells III, WM, Kikinis R: Segmentation of brain tissue from magnetic resonance images. Med Image Anal 1(2):109–127, 1996
Atkins MS, Mackiewich B: Fully automatic segmentation of the brain in MRI. IEEE Transactions Med Imaging 17(1):98–107, 1998
Abramoff MD, Magelhaes PJ, Ram SJ: Image processing with image. J Biophotonics International 11(7):36–42, 2004
Bauer S, Fejes T, Reyes M: A skull-stripping filter for ITK, Insight Journal, 2012. http://hdl.handle.net/10380/3353
Rehm K, Schaper K, Anderson J, Woods R, Stoltzner S, Rottenberg D: Putting our heads together: a consensus approach to brain/Non-brain segmentation in T1-weighted MR volumes. NeuroImage 22(3):1262–1270, 2004
Woods RP, Grafton ST, Watson JDG, Sicotte NL, Mazziotta JC: Automated image registration: II intersubject validation of linear and nonlinear models. J Comput Assist Tomogr 22(1):153–165, 1998
Segonne F, Dale AM, Busa E, Glessner M, Salat D, Hahn HK, Fischl B: A hybrid approach to the skull stripping problem in MRI. NeuroImage 22(3):1060–1075, 2004
Rex DE, Shattuck DW, Woods RP, Narr KL, Luders E, Rehm K, Stolzner SE, Rotten-berg DA, Toga AW: A meta-algorithm for brain extraction in MRI. NeuroImage 23(2):625–637, 2004
Shi F, Wang L, Gilmore JH, Lin W, Shen D: Learning-based meta-algorithm for MRI brain extraction, Proc. medical image computing and computer assisted intervention (MICCAI). LNCS 6893:313–321, 2011
Huang A, Abugharbieh R, Tam R, Traboulsee A: MRI brain extraction with combined expectation maximization and geodesic active contours. Proc. IEEE Int Symp Signal Proc Inf Technol 107(1):107–111, 2006
Carass A, Cuzzocreo J, Wheeler MB, et al: A joint registration and segmentation approach to skull stripping, Proc. IEEE Symposium on Biomedical Imaging. 655-659,2007
Iglesias JE, Liu CY, Thompson PM, Tu Z: Robust brain extraction across datasets and comparison with publicly available methods. IEEE Trans Med Imaging 30(9):1617–1634, 2011
Lee JM, Yoon U, Nam SM, Kim JH, Kim IY, Kim SI: Evaluation of automated and semi-automated skull stripping algorithms using similarity index and segmentation error. Comput Biol Med 33(6):495–507, 2003
Boesen K, Rehm L, Schaper K, Stoltzner S, Woods R, Luders E, Rottenberg D: Quan- titative comparison of four brain extraction algorithms. NeuroImage 22(3):1255–1261, 2004
Hartley SW, Scher AI, Korf ESC, White LR, Launer LJ: Analysis and validation of automated skull stripping tools: a validation study based on 296 MR images from Honolulu Asia aging study. NeuroImage 30(4):1179–1186, 2006
Shattuck DW, Prasad G, Mirza M, Narr KL, Toga AW: Online resource for validation of brain segmentation methods. NeuroImage 45(2):431–439, 2009
Richard A: Biomedical imaging, visualization and analysis. John Wiley & Sons Inc, New York, USA, 2000
Yoon UC, Kim JS, Kim IY, Kim SI: Adaptive fuzzy C-means for improved classification as a preprocessing procedure of brain parcellation. J Digit Imaging 14(2):238–240, 2001
Sled JG, Zijdenbos AP, Evans AC: A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Trans Med Imaging 17(1):87–97, 1998
Somasundaram K, Kalavathi P: Medical image denoising using Non-linear spatial mean filters for edge detection. Proc. Signal and Image Processing, New Delhi, 2012, pp 149–154
Somasundaram K, Kalavathi P: Analysis of imaging artifacts in MR brain images. Oriental J Comput Sci Technol 5(1):135–141, 2012
Somasundaram K, Kalavathi P: Medical image contrast enhancement based on gamma correction. Int J Knowl Manag e-learning 3(1):15–18, 2011
ANALYZE 12.0 – Visualization and analysis software for medical imaging. Available at : http://analyzedirect.com/analyze-12-0/
Speier W, Iglesias JE, El-Kara L, Tu Z, Arnold C: Robust skull stripping of clinical glioblastoma multiforme data, Proc. medical image computing and computer assisted intervention (MICCAI). LNCS 6893:659–666, 2011
Bauer S, Nolte L-P, Reyes M: Skull-stripping for tumor-bearing brain images. In Philippe Buchler and Stephen Ferguson, editors, Annual Meeting of the Swiss Society for Biomedical Engineering, page 2, Bern, April 2011. SSBE