2003, Number 2
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Rev Mex Ing Biomed 2003; 24 (2)
The Finite Element Method for the Registration of Magnetic Resonance Images
Botello S, Marroquín JL
Language: Spanish
References: 23
Page: 104-115
PDF size: 251.56 Kb.
ABSTRACT
Image registration is a problem that has not been solved yet in a precise form, and has applications in different fields of image processing, including the processing of magnetic resonance images. In this work, we present some novel ideas on the application of the Finite Element Method to the solution of this problem, which improve the computed deformation fields (both for small and large deformations) that register a set of images. To show the behaviour of our method, we include results on both synthetic and real images. We also include applications to 3-D image registration that use an intensity correction technique, which are useful in the processing of functional MRI, where the precise localization of brain regions that activate under a stimulus is very important.
REFERENCES
Cocosco CA, Kollokian V, Kwan RK, Evans AC. Brian Web: On line Interface to a 3D MRI Simulated Brain Database, Neuroimage 1997: 5, 4, part 2/4, S425.
Maintz JBA, Vierger MA. A survey of Medical Image Registration, Medical Image Analysis 1998; 2(1): 1-36.
Viola P, Wells III WM. Alignment by Maximization of Mutual Information. Int Jour Comp Vision 1997; 24(2): 137-154.
Meyer C et al. Demonstration of accuracy and clinical versatility of mutual information for automatic multimodality image fusion ussing affine and thin-plate sline-warped geometric deformations. Medical Image Analysis 1997; 1: 195-206.
Rueckert D, Sonda LI, Hill DLG, Hqayes C, Leach MO, Hawkes DJ. Nonrigid registration using free-form deformation: Application to breast MR images, IEEE Trans. on Medical Images 1999; 18(8): 712-721.
Bajscy R, Kovacic S. Multiresolution elastic maching, Computer Vision. Graphics and Image Processing 1989; 46: 1-21.
Christensen GE, Miller MI, Vannier M. Individualizing neuroanatomical atlases using a massively pararel computer. IEEE Computer. 1996; 1(29): 32-38.
Szeliski R, Coughlan J. Hierarchical spline-based image registration, IEEE conf. Comput. Vision Patt Recog 1994: 194-201.
Vemuri BC et al. An efficient motion estimator with application to medical image registration. Medical Image Analysis 1998; 2(1): 79-98.
Kumar A, Tannenbaum A, Balas G. Optical flow: A curve evolution approach, IEEE Trans. on Image Processing 1996; 5(4): 598-610.
Vemuri BC, Ye J, Chen Y, Leonard CM. A level-set based approach to image registration, IEEE Workshop on Mathematical Methods in Biomedical Image Analysis, 2000: 86-93.
Scales LE. Introduction to Non-Linear Optimization, Liverpool UK. Department of Computer Science University of Liverpool. 1984.
Nocedal J, Wright SJ. Numerical Optimization, Springer, New York, 1999.
Oñate E. Cálculo de estructuras por el método de los elementos finitos. Análisis Estático Lineal, CIMNE Primera Edición 1992.
Marroquín JL, Venuri BC, Botello S, Calderón F, Fernández BA. An accurate and efficient bayesian method for automatic segmentation of brain MRI. IEEE Trans. on Medical Imaging. 2002; 21(8): 934-945.
Romeny BMTH. Geometry-Driven diffusion in computer vision. Dordrecht, The Netherlands, Kluwer Academic Press, 1994.
Unser M. Splines. A perfect fitfor signal and image processing, IEEE Signal Processing Magazine, 1999: 22-38.
Maes F, Collignon A, Vandermeulen D, Marchal G, Suetens P. Multimodality image registration by maximization of mutual information, IEEE transactions on Medical Imaging, 1997; 16: 2, 187-198.
Friston KJ, Ahsburner J, Frith CD, Poline JB, Heather JD, Frackowiak RSJ. Spatial registration and normalization of images. Hum Brain Map 1995; 2: 165-189.
Fraire L, Mangin JF. Motion correction algorithms of the brain mapping community create spurius functional activations, Proc. Information Processing in Medical Imaging, IPMI , Davis. CA, USA 2001.
Press WH, Teukolsky SA, Vetterling WT, Flannery BP. Numerical Recipes in C, Second Edition. Cambridge University Press, 1992.
Salomon M, Perrin GR, Heitz F. Differencial evolution for medical image registration, Inter. Conf. on Artificial Intelligence, Las Vegas, 2001.
Briggs W. A multigrid tutorial, society for industrial and applied mathematics. Lancaster Press 1988.