Image registration of sectioned brains

International Journal of Computer Vision

Volumn 73, Issue 1, 2007, Pages 5-39

  Schmitt, Oliver ^a   Modersitzki, Jan ^b   Heldmann, Stefan ^b   Wirtz, Stefan ^b   Fischer, Bernd ^b  

^a UNIVERSITY OF ROSTOCK   (Germany)

^b UNIVERSITY OF LÜBECK   (Germany)

Author keywords

3D reconstruction; Affine registration; Alignment; Elastic registration; Human and rat brain serial sections; Matching; Neuroimaging; Warping

Indexed keywords

ANALOG TO DIGITAL CONVERSION; BRAIN; CELLS; HISTOLOGY; IMAGE ANALYSIS; PATTERN MATCHING;

AFFINE REGISTRATION; HISTOLOGIC SECTIONS; IMAGE ALIGNMENT; IMAGE REGISTRATION; NEUROIMAGING; REGISTRATION METHODS;

MEDICAL IMAGING;

EID: 33846616247     PISSN: 09205691     EISSN: 15731405     Source Type: Journal    
DOI: 10.1007/s11263-006-9780-x     Document Type: Article

References (188)

1. Abbe, E. 1873. Beiträge zur Theorie des Mikroskops und der mikroskopischen Wahrnehmung. Arch. Mikr. Anat., 9:413.
2. Abeles, M. 1991, Corticonics. Neural circuits of the cerebral cortex. Cambridge University Press: Cambridge.
3. Aferzon, J., Chau, R., and Cowan, D. 1991. A microcomputer-based system for three-dimensional reconstructions from tomographic or histologie sections. Anal. Quant. Cytol. Histol., 13:80-88.
4. Alexander, M., Scarth, G., and Somorjai, R. 1997. An improved robust hierarchical registration algorithm. Magn. Reson. Imaging., 15:505-514.
5. Alpert, N., Bradshaw, J., Kennedy, D., and Correia, J. 1990. The principal axes transformation - a method for image registration. J. Nuc. Med., 31:1717-1722.
6. Amit, Y., Grenander, U., and Piccioni, M. 1991. Structural image restoration through deformable templates. J. Am. Stat. Ass., 86:376-387.
7. Arbib, M. 1995, The Handbook of Brain Theory and Neural Networks. MIT Press: Cambridge.
8. Arsigny, V., Pennec, X., and Ayache, N. 2005. Polyrigid and polyaffine transformations: A novel geometrical tool to deal with non-rigid deformations - Application to the registration of histological slices. Med. Image. Anal., 9:507-523.
9. Ashburner, J., Andersson, J., and Friston, K. 2000. Image registration using a symmetric prior-in three dimensions. Hum. Brain. Mapp., 9:212-225.
10. Auer, M., Regitnig, P., and Holzapfel, G. 2005. An automatic nonrigid registration for stained histologic sections. IEEE Trans. Imag. Proc., 14:475-486.
11. Baheerathan, S., Albregtsen, F., and Danielsen, H. 1998. Registration of serial sections of mouse liver cell nuclei. J. Microsc., 192:37-53.
12. Bajcsy, R. 1982. Matching of deformed images. Proc. 6th Int. Conf. Patt. Recogn., 6:351-353.
13. Bajcsy, R. 1983. A computerized system for the elastic matching of deformed radiographic images to idealized atlas images. J. Comp. Ass. Tomo., 7:618-625.
14. Bajcsy, R. and Kovačíč, S. 1989. Multiresolution elastic matching. Comp. Vis. Image. Proc., 46:1-21.
15. Banerjee, P. and Toga, A. 1994. Image alignment by integrated rotational and translational transformation matrix. Phys. Med. Biol., 39:1969-1988.
16. Bardinet, E., Colchester, A., Roche, A., Zhu, Y., He, Y., Ourselin, S., Nailon, B., Hojjat, S., Ironside, J., Al-Sarraj, S., Ayache, N., and Wardlaw, J. 2001. Registration of reconstructed post mortem optical data with MR scans of the same patient. LNCS, 2208:957-965.
17. Barnard, S. and Thompson, W. 1980. Disparity analysis of images. IEEE Trans. PAMI, 2:333-340.
18. Barnea, D. and Silverman, H. 1972. A class of algorithms for fast digital image registration. IEEE Trans. Comp., 21:179-186.
19. Baumann, M. and Scharf, H. 1994. Moderne Bildverarbeitungsverfahren als Unterstützung der räumlichen Rekonstruktion histologischer Strukturen. Ann. Anat., 176:185-188.
20. Benveniste, H. and Blackband, S. 2002. MR microscopy and high resolution small animal MR1: Applications in neuroscience research. Prog. Neurobiol, 67:393-420.
21. Böhme, M., Hagenau, R., Modersitzki, J., and Siebert, B. 2002. Nonlinear image registration on PC-clusters using parallel FFT techniques. Technical Report SIIM-TR-A-02-08, Institute of Mathematics, Medical University of Lübeck.
22. Bookstein, F. 1984. A statistical method for biological shape comparisons. J. Theor. Biol., 107:475-520.
23. Bookstein, F. 1989. Principal warps: Thin-plate splines and the decomposition of deformations. IEEE Trans. Patt. Anal. Mach. Intell., 11:567-585.
24. Borgefors, G. 1988. Hierarchical chamfer matching: A parametric edge matching algorithm. IEEE Trans. PAMI, 10:849-865.
25. Born, G. 1883. Die Plattenmodellirungsmethode. Arch. Mikr. Anat., 22:584-599.
26. Braitenberg, V. 1978. Cell assemblies in the cerebral cortex. Lec. Notes. Biomath., 21:171-188.
27. Bro-Nielsen, M. and Gramkow, C. 1996. Fast fluid registration of medical images. LNCS, 1131:261-216.
28. Broit, C. 1981. Optimal registration of deformed images. Ph.D. thesis, Computer and Information science, University of Pensylvania.
29. Bron, C., Launay, D., Jourlin. M., Gautschi, H., Bächi, T., and Schüpbach, J. 1990. Three dimensional electron microscopy of entire cell. J. Mircosc., 157:115-126.
30. Brown, L. 1992. A survey of image registration techniques. ACM Comp. Surv., 24:325-376.
31. Budo, A. 1990, Theoretische Mechanik. VEB Deutscher Verlag der Wissenschaften.
32. Christensen, G. 1994. Deformable shape models for anatomy. Ph.D. thesis, Sever Institute of Technology, Washington University.
33. Christensen, G. and Johnson, H. 2001. Consistent image registration. IEEE Trans. Med. Imaging., 20:568-582.
34. Christensen, G., Joshi, S., and Miller, M. 1997. Volumetric transformation of brain anatomy. IEEE Trans. Med. Imaging., 16:864-877.
35. Chui, H., Win, L., Schultz, E., Duncan, J., and Rangarajan, A. 2001. A unified feature registration method for brain mapping. LNCS, 2082:300-314.
36. Ciarlet, P. 2000. Mathematical Elasticity. Elsevier Science.
37. Cohen, F., Yang, Z., Huang, Z., and Nissanov, J. 1998. Automatic matching of homologous histological sections. IEEE Trans. Biomed. Eng., 45:642-649.
38. Collins, D., Holmes, C., Peters, H., and Evans, A. 1995. Automatic 3D model-based neuroanatomical segmentation. Hum. Brain. Mapp., 3:190-208.
39. Dauguet, J., Mangin, J.-K, Delzescaux, T., and Frouin, V. 2004. Robust inter-slice intensity normalization using histogram scalespace analysis. LNCS, 3216:242-249.
40. Davatzikos, C. 1997. Spatial transformation and registration of brain images using elastically deformable models. Comput. Vis. Image. Underst., 66:207-222.
41. Davatzikos, C. and Prince, J. 1994. Brain image registration based on curve mapping. Proc. IEEE Workshop. Biom. Image. Anal., 245-254.
42. de Castro, E. and Morandi, C. 1987. Registration of translated and rotated images using finite Fourier transforms. IEEE Trans. PAMI, 9:700-703.
43. de Munck, J., Verster, F., Dubois, E., Habraken, J., Boltjes, B., Claus, J., and van Herk, M. 1998. Registration of MR and SPECT without using external fiducial markers. Phys. Med. Biol., 43:1255-1269.
44. Desgeorges, M., Derosier, C., Cordoliani, Y., Traina, M., de Soultrait, F., Bernard, C., Khadiri, M., and Debono, B. 1997. Imaging networks, surgical simulation, computer-assisted neurosurgery. J. Neuroradiol., 24:108-115.
45. Dierker, M. 1976, An Algorithm for the Alignment of Serial Sections. John Wiley & Sons: New York, P.B. Brown: Computer technology on neuroscience edition.
46. Dougherty, E. 1993, Mathematical Morphology in Image Processing. Marcel Dekker: New York, Basel, Hong Kong.
47. du Bois d'Aische, A., Craene, M. D., Geets, X., Gregoire, V., Macq, B., and Warfield, S. 2005. Efficient multi-modal dense field nonrigid registration: Alignment of histological and section images. Med. Image. Anal., 9:538-546.
48. Ferrant, M., Nabavi, A., Macq, B., Jolesz, F., Kikinis, R., and Warfield, S. 2001. Registration of 3-D intraoperative MR images of the brain using a finite-element biomechanical model. IEEE Trans. Med. Imaging., 20:1384-1397.
49. Fischer, A. and Modersitzki, J. 1999. Fast inversion of matrices arising in image processing. Num. Algo., 22:1-11.
50. Fischer, A. and Modersitzki, J. 2001. A super fast registration algorithm. BVM, 22:168-173.
51. Fischer, A. and Modersitzki, J. 2002. Fast diffusion registration. Contemp. Math., 313:117-129.
52. Fischer, M. and Elschlager, R. 1973. The representation and matching of pictorial structure. IEEE Trans. Comput., 1:67-92.
53. Fortner. 1999. User's Guide and Reference Manual. Fortner Software: Boulder.
54. Fu, Y. and Ogden, R. 2001. Nonlinear Elasticity: Theory and Applications. Cambridge University Press: Cambridge.
55. Gefen, S., Tretiak, O., and Nissanov, J. 2003. Elastic 3-D alignment of rat brain histological images. IEEE Trans. Med. Imag., 22:1480-1489.
56. Gerstein, G., Bedenbaugh, P., and Aertsen, A. 1989. Neuronal assemblies. IEEE Trans. Biomed. Engin., 36:4-14.
57. Glaser, J. and Glaser, M. 1965. A semi-automatic computer-microscope for the analysis of neuronal morphology. IEEE Trans. Biomed. Eng., 12:22-31.
58. Gold, S., Rangarajan, A., Lu, C., Pappu, S., and Mjolsness, E. 1998. New algorithms for 2-D and 3-D point matching: pose estimation and correspondence. Pat. Recogn., 31:1019-1031.
59. Golub, G. and van Loan, C. 1989. Matrix Computations. Second edition. The John Hopkins University Press: Baltimore.
60. Green, A. and Adkins, J. 1970. Large Elastic Deformations. Clarendon Press: Oxford.
61. Green, A. and Zerna, W. 1968. Theoretical Elasticity. Clarendon Press: Oxford.
62. Gremillet, P., Bron, C. Jourlin, M., Bachi, T., and Schüpbach, J. 1991. Dedicated image analysis techniques for three-dimensional reconstruction from serial sections in electron microscopy. Mach. Vis. Appl., 4:263-270.
63. Guimond, A., Roche, A., Ayache, N., and Meunier, J. 2001. Three-dimensional multimodal brain warping using the demons algorithm and adaptive intensity corrections. IEEE Trans. Med. Imaging., 20:58-69.
64. Hajnal, J., Saeed, N., Soar, E., Oatridge, A., Young, I., and Bydder, G. 1995. A registration and interpolation procedure for subvoxel matching of serially acquired MR images. J. Comput. Assist. Tomogr., 19:289-296.
65. Hamilton, P., McInerney, T., and Terzopoulos, D. 2001. Deformable organisms for automatic medical image analysis. LNCS, 2208:66-76.
66. Hayakawa, N., Thevenaz, P., Nirkko, A., Uemura, M.U., Ishiwata, K., Shimada, Y, Ogi, N., Nagaoka, T., Toyama, H., Oda, K., Tanaka, A., Endo, K., and Senda, M. 2000. A PET-MRI registration technique for PET studies of the rat brain. Nucl. Med. Biol., 27:121-125.
67. Hebb, D. 1949, The Organization of Behavior. Wiley: New York.
68. Hellier, P., Barillot, C., Memin, E., and Perez, P. 2001. Hierarchical estimation of a dense deformation field for 3-D robust registration. IEEE Trans. Med. Imaging., 20:388-402.
69. Hibbard, L., Arnicar-Sulze, T., Dovey-Hartman, B., and Page, R. 1992. Computed alignment of dissimilar images for three-dimensional reconstructions. J. Neurosci. Methods., 41:133-152.
70. Hibbard, L., and Hawkins, R. 1988. Objective image alignment for three-dimensional reconstruction of digital autoradiograms. J Neurosci. Meth., 26:55-74.
71. Hibbard, L., McGlone, J., Davis, D., and Hawkins, R. 1987. Three-dimensional representation and analysis of brain energy metabolism. Science, 236:1641-1646.
72. Hill, D., Batchelor, P., Holden, M., and Hawkes, D. 2001. Medical image registration. Phys. Med. Biol., 46:R1-R45.
73. Hoehn, M., Küstermann, E., Blunck, J., Wiedermann, D., Trapp, T., Wecker, S., Föking, M., Arnold, H., Hescheler, J., Fleischmann, B., Schwindt, W, and Bührle, C. 2002. Monitoring of implanted stem cell migration in vivo: a highly resolved in vivo magnetic resonance imaging investigation of experimental strocke in rat. Proc. Nat. Acad. Sci., 99:16267-16272.
74. Holden, M., Hill, D.H., Denton, E., Jarosz, J., Cox, T., Rohlfing, T., Goodey, J., and Hawkes, D. 2000. Voxel similarity measures for 3-D serial MR brain image registration. IEEE Trans. Med. Imaging., 19:94-102.
75. Horn, B. and Schunck, B. 1981. Determining optical flow. Art. Intell., 17:185-204.
76. Hsu, C., Wu, M., and Lee, C. 2001. Robust image registration for functional magnetic resonance imaging of the brain. Med. Biol. Eng. Comput., 39:517-524.
77. Hu, M. 1962. Visual pattern recognition by moment invariants. IEEE Trans. Inform. Theory., 8:179-187.
78. Iosifescu, D., Fitzpatrick, J., Wang, M., Galloway, R.J., Maciunas, R., Allen, G., Shenton, M., Warfield, S., Kikinis, R., Dengler, J., Jolesz, F., and McCarley, R. 1997. An automated registration algorithm for measuring MRI subcortical brain structures. Neuroimage, 6:13-25.
79. Jacobs, M., Windham, J., Soltanian-Zadeh, H., Peck, D., and Knight, R. 1999. Registration and warping of magnetic resonance images to histological sections. Med. Phys., 26:1568-1578.
80. Jannin, P., Fleig, O., Seigneuret, E., Grova, C., Morandi, X., and S carabin, J. 2000. A data fusion environment for multimodal and multi-informational neuronavigation. Comput. Aided, Surg., 5:1-10.
81. Johnson, E. and Capowski, J. 1983. A system for the three-dimensional reconstruction of biological structures. Comp. Biomed. Res., 16:79-87.
82. Johnson, H. and Christensen, G. 2001. Landmark and intensitybased, consistent thin-plate spline image registration. LNCS, 2082:329-343.
83. Joshi, S. and Miller, M. 2000. Landmark matching via large deformation diffeomorphisms. IEEE Trans. Image. Proc., 9:1357-1370.
84. Juan, M., Alcaniz, B., Hernandez, V., Montesinos, A., Barcia, J., Monserrat, C., and Grau, V. 2000. A new efficient method for 3D registration using human brain atlases. Stud. Health. Technol. Inform., 70:153-155.
85. Kent, J. and Tyler, D. 1988. Maximum likelihood estimation for the wrapped Cauchy distribution. J. Appl. Stat., 15:247-254.
86. Kiebel, S., Ashburner, J., Poline, J., and Friston, K. 1997. MRI and PET coregistration-a cross validation of statistical parametric mapping and automated image registration. Neuroimage, 5:271-279.
87. Kosevich, A. 1995, Theory of Elasticity. 3rd Ed. Butterworth Heinemann, Oxford.
88. Kostelec, P., Weaver, J., and Healy, D. J. 1998. Multiresolution elastic image registration. Med. Phys., 25:1593-1604.
89. Kremser, C., Plangger, C., Boesecke, R., Pallua, A., Aichner, F., and Felber, S. 1997. Image registration of MR and CT images using a frameless fiducial marker system. Mag. Res. Imag., 15:579-585.
90. Kuglin, C. and Hines, D. 1975. The phase correlation image alignment method. Proc. IEEE Int. Conf. Cyb. Soc., 163-165.
91. Kuljis, R. and Rakic, P. 1990. Hypercolumns in primate visual cortex can develop in the absence of cues from photoreceptors. Proc. Natl. Acad. Sci. USA, 87:5303-5306.
92. Kullback, S. and Leibler, R. 1951. On information and sufficiency. Ann. Math. Statist., 122:79-86.
93. Lamadø, W., Glombitza, G., Demiris, A., Cardenas, C., Thorn, M., Meinzer, H., Grenacher, L., Bauer, H., Lehnert, T., and Herfarth, C. 2000. The impact of 3-dimensional reconstructions on operation planing in liver surgery. Arch. Surg., 135:1256-1261.
94. Lester, H. and Arridge, S. 1999. A survey of hierarchical non-linear medical image registration. Pat. Rec., 32:129-149.
95. Likar, B. and Pernus, F. 1999. Automatic extraction of corresponding points for the registration of medical images. Med. Phys., 26:1678-1686.
96. Lurie, A. 1990, Nonlinear Theory of Elasticity. North-Holland: Amsterdam.
97. Macagno, E., Levinthal, C., and Sobel, I. 1979. Three-dimensional computer reconstruction of neurons and neuronal assemblies. Annu. Rev. Biophys. Bioeng., 8:323-351.
98. Macagno, E., Levinthal, C., Tountas, C., Bornholdt, R., and Abba, R. 1976, Recording and Analysis of 3-D Information fiom Serial Section Micrographs: The. Cartos System. Hemisphere Publishing Corporation: Washington, P.B. Brown: Computer technology in neuroscience edition.
99. MacDonald, D., Kabani, N., Avis, D., and Evans, A. 2000. Automated 3d extraction of inner and outer surfaces of cerebral cortex from MRI. NeuroImage, 12:340-356.
100. Maintz, J. and Viergever, M. 1981. A survey of medical image registration. Med. Image. Anal., 2:1-36.
101. Malandain, G. and Bardinet, E. 2003. Intensity compensation within series of images. LNCS, 2879:41-49.
102. Malandain, G., Bardinet, E., Nelissen, K., and Vanduffel, W. 2004. Fusion of autoradiographs with an MR volume using 2-D and 3-D linear transformations. NeuroImage, 23:111-127.
103. Maurer, C. and Fitzpatrick, J. 1993. Interactive Image-Guided Neurosurgety. R.J. Maciunas (Ed.). A review of medical image registration, American Association of Neurological Surgeons, Park Ridge, IL, pp. 17-44.
104. Maurer, C., Fitzpatrick, J., Wang, M., Galloway, R., Maciunas, R., and GS, G.A. 1997. Registration of head volume images using implantable fiducial markers. IEEE Trans. Med. Imag., 16:447-462.
105. Maurer, C., Hill, D., Martin, A., Liu, H., McCue, M., Rueckert, D., Lloret, D., Hall, W., Maxwell, R., Hawkes, D., and Truwit, C. 1998a. Investigation of intraoperative brain deformation using a 1.5-T interventional MR system: preliminary results. J. Anat., 193:347-361.
106. Maurer, C., Hill, D., Martin, A., Liu, H., McCue, M., Rueckert, D., Lloret, D., Hall, W., Maxwell, R., Hawkes, D., and Truwit, C. 1998b. Investigation of intraoperative brain deformation using a 1.5-T interventional MR system: preliminary results. IEEE Trans. Med. Imaging., 17:817-825.
107. Maurer, C., Maciunas, R., and Fitzpatrick, J. 1998c. Registration of head CT images to physical space using a weighted combination of points and surfaces. IEEE Trans. Med. Imaging., 17:753-761.
108. McInerney, J. and Roberts, D. 1998. An object-based volumetric deformable atlas for the improved localization of neuroanatomy in MR images. LNCS, 1496:861-869.
109. Mega, M., Berdichevsky, D., Levin, Z., Morris, E., Fischman, A., Chen, S., Thompson, P., Woods, R., Karaca, T., Tiwari, A., Vinters, H., Small, G., and Toga, A. 1997. Mapping histology to metabolism: Coregistration of stained whole-brain sections to premortem PET in Alzheimer's disease. Neuroimage, 5:147-153.
110. Miller, K. and Chinzei, K. 1997. Constitutive modelling of brain tissue: experiment and theory. J. Biomech., 30:1115-1121.
111. Modersitzki, J. 2004, Numerical Methods for Image Registiation. Oxford University Press.
112. Modersitzki, J., Obelöer, W., Schmitt, O., and Lustig, G. 1999. Elastic matching of very large digital images on high performance clusters. LNCS, 1593:141-149.
113. Mountcastle, V. 1997. The columnar organization of the neocortex. Brain, 120:701-722.
114. Murphy, M., O'Brien, T., Morris, K., and Cook, M. 2001. Multimodality image-guided epilepsy surgery. J. Clin. Neurosci., 8:534-538.
115. Mutic, S., Hellier, P., Barillot, C., Dempsey, J., Bosch, W., Low, D., Drzymala, R., Chao, K., Goddu, S., Cutler, P., and Purdy, J. 2001. Multimodality image registration quality assurance for conformal three-dimensional treatment planning. Int. J. Radiat. Oncol. Biol. Phys., 51:255-260.
116. Nowinski, W., Scarth, G., Somorjai, R., Fang, A., Nguyen, B., Raphel, J., Jagannathan, L., Raghavan, R., Bryan, R., and Miller, G. 1997. Multiple brain atlas database and atlas-based neuroimaging system. Comput. Aided. Surg., 2:42-66.
117. Nowinski, W. and Thirunavuukarasuu, A. 2001. Atlas-assisted localization analysis of functional images. Med. Image. Anal., 5:207-220.
118. Okajima, K. 1986. A mathematical model of the primary cortex and hypercolumn. Biol. Cyber., 54:107-114.
119. Ongaro, I., Sperber, G., Machin, G., and Murdoch, C. 1991. Fiducial points for three-dimensional computer-assisted reconstruction of serial light microscopic sections of umbilical cord. Anat. Rec., 229:285-289.
120. Otte, M. 2001. Elastic registration of fMRI data using Bezier-spline transformations. IEEE Trans. Med. Imaging., 20:193-206.
121. Ourselin, S., Bardinet, E., Dormont, D., Malandain, G., Roche, A., Ayache, N., Tandé, D. Parain, K., and Yelnik, J. 2001a. Fusion of histological sections and MR images: towards the construction of an atlas of the human basal ganglia. LNCS, 2208:743-751.
122. Ourselin, S., Roche, A., Subsol, G., Pennec, X., and Ayache, N. 200 Ib. Reconstructing a 3D structure from serial histologic sections. Image. Vis. Comp., 19:25-31.
123. Ozturk, C. 2002. Align 1.1. http://www.neuroterrain.org/~webby/ production/body/index.html.
124. Palm, G. 1982, Studies of Brain Function: Neural Assemblies. Springer: Berlin.
125. Pawley, J. 1995, Handbook of Biological Confocal Microscopy. Plenum: New York.
126. Penney, G., Weese, J., Little, J., Desmedt, P., Hill, D., and Hawkes, D. 1998. A comparison of similarity measures for use in 2-D-3-D medical image registration. IEEE Trans. Med. Imaging., 17:586-595.
127. Perkins, W. and Green, R. 1982. Three-dimensional reconstruction of biological sections. J. Biomed. Eng. 4:37-43.
128. Rangarajan, A., Chui, H., and Duncan, J. 1999. Rigid point feature registration using mutual information. Med. Image. Anal., 3:425-440.
129. Rangarajan, A., Chui, H., Mjolsness, E., Pappu, S., Davachi, L., Goldman-Rakic, P., and Duncan, J. 1997. A robust point matching algorithm for autoradiographic alignment. Med. Image. Anal., 4:379-398.
130. Rohlflng, T. and Maurer, C. 2001. Intensity-based non-rigid registration using adaptive multilevel free-form deformation with an incompressibility constraint. LNCS, 2208:111-119.
131. Rohlfing, T., West, J., Beier, J., Liebig, T., Taschner, C., and Thomale, U. 2000. Registration of functional and anatomical MRI: accuracy assessment and application in navigated neurosurgery. Comput. Aided. Surg., 5:414-425.
132. Rohr, K., Stiehl, H., Sprengel, R., Buzug, T., Weese, J., and Kuhn, M. 2001. Landmark-based elastic registration using approximating thin-plate splines. IEEE Trans. Med. Imaging., 20:526-534.
133. Rouet, J., Jacq, J., and Roux, C. 2000. Genetic algorithms for a robust 3-D MR-CT registration. IEEE Trans. Inf. Technol. Biomed., 4:126-136.
134. Rueckert, D., Sonoda, L., Hayes, C., Hill, D., Leach, M., and Hawkes, D. 1999. Nonrigid registration using free-form deformations: application to breast MR images. IEEE Trans. Med. Imaging., 18:712-721.
135. Rusinek, H., Tsui, W.-H., Levy, A., Noz, M., and de Leon, M. 1993. Principal axes and surface fitting methods for three-dimensional image registration. J. Nuc. Med., 34:2019-2024.
136. Russo, R. 1996, Mathematical Problems in Elasticity. World Scientific Publ: Singapore.
137. Sabbah, P., Zagrodsky, V., Foehrenbach, H., Dutertre, G., Nioche, C., DeDreuille, O., Bellegou, N., Mangin, J., Leveque, C., Faillot, T., Gaillard, J., Desgeorges, M., and Cordoliani, Y. 2002. Multimodal anatomic, functional, and metabolic brain imaging for tumor resection. Clin. Imaging., 26:6-12.
138. Santori, E. and Toga, A. 1993. Superpositioning of 3-dimensional neuroanatomic data sets. J. Neurosci. Methods., 50:187-196.
139. Schieweck, F. 1993. A parallel multigrid algorithm for solving the Navier-Stockes equations. Imp. Comp. Sci. Eng., 5:345-378.
140. Schlaug, G., Schleicher, A., and Zilles, K. 1995. Quantitative analysis of the columnar arrangement of neurons in the human cingulate cortex. J. Comp. Neurol., 351:441-452.
141. Schmitt, O. and Eggers, R. 1997a. High contrast and homogeneous staining of paraffin sections of whole human brains for three dimensional ultrahigh resolution image analysis. Biotech. Histochem., 73:44-51.
142. Schmitt, O. and Eggers, R. 1997b. Systematic investigations of the contrast results of histochemical stainings of neurons and glial cells in the human brain by means of image analysis. Micron, 28:197-215.
143. Schmitt, O. and Eggers, R. 1999. Flat-bed scanning as a tool for quantitative neuroimaging. J. Microsc., 196:337-346.
144. Schmitt, O., Eggers, R., and Modersitzki, J. 2005. Videomicroscopy, image processing, and analysis of whole histologic sections of the human brain. Micr. Res. Tech., 66:203-218.
145. Schmitt, O., Modersitzki, J., and Obelöer, W. 1999. The human neuroscanning project. Neuroimage, 9:S22.
146. Schmolke, C. 1996. Tissue compartments in laminae II-V of rabbit visual cortex-three-dimensional arrangement, size and developmental changes. Anat. Embiyol., 193:15-33.
147. Schmolke, C. and Fleischhauer, K. 1984. Morphological characteristics of neocortical laminae when studied in tangential semithin sections through the visual cortex of the rabbit. Anat. Embryol., 169:125-133.
148. Schormann, T. 1996. A new approach to fast elastic alignment with applications to human brains. LNCS, 1131:337-342.
149. Schormann, T., Darbinghaus, A., and Zilles, K. 1997. Extension of the principle axes theory for the determination of affine transformations. Informatik aktuell, 19:384-391.
150. Schormann, T. and Zilles, K. 1997. Limitations of the principal axes theory. IEEE Trans. Med. Imag., 16:942-947.
151. Schormann, T. and Zilles, K. 1998. Three-dimensional linear and nonlinear transformations: an integration of light microscopical and MR1 data. Hum. Brain. Mapp., 6:339-347.
152. Silva, A. and Koretsky, A. 2002. Laminar specificity of functional MRI onset times during somatosensory stimulation in rat. Proc. Nat. Acad. Sci., 99:15182-15187.
153. Sjöstrand, R. 1958. Ultrastructure of retinal rod synapses of the guinea pig eye as revealed by 3-D reconstructions from serial sections. J. Ultrastruct. Res., 2:122-170.
154. Sokolnikoff, I. 1956, Mathematical Theory of Elasticity. McGraw-Hill: New York.
155. Street, C. and Mize, R. 1983. A simple microcomputer-based three-dimensional serial reconstruction system (MICROS). J. Neurosci. Meth., 7:359-375.
156. Studholme, C., Hill, D., and Hawkes, D. 1999. An overlap invariant entropy measure of 3D medical image alignment. Pat. Recog., 32:71-86.
157. Symon, K. 1971, Mechanics. 3rd edition, Addison-Wesley: Reading, MA.
158. Tanaka, S. 1991. Theory of ocular dominance column formation. Biol. Cyber., 64:263-272.
159. Thirion, J.-P. 1998. Image matching as a diffusion process: An analogy with Maxwell's demons. Med. Image. Anal., 2:243-260.
160. Thompson, J., Peterson, M., and Freeman, R. 2003. Single-Neuron activity and tissue oxygenation in the cerebral cortex. Science, 299:1070-1072.
161. Thompson, M. and Ferziger, J. 1989. An adaptive multigrid technique for the incompressible Navier-Stockes equations. J. Comp. Phys., 82:94-121.
162. Thurfjell, L., Bohm, C., and Bengtsson, E. 1995. CBA-an atlasbased software tool used to facilitate the interpretation of neuroimaging data. Comput. Methods. Programs. Biomed., 47:51-71.
163. Toga, A. and Banerjee, P. 1993. Registration revisited. J. Neurosci. Meth., 48:1-13.
164. Toga, A., Santori, E., Hazani, R., and Ambach, K. 1995. A 3D digital map of rat brain. Brain. Res. Bull., 38:77-85.
165. Toga, A. and Thompson, P. 2001. The role of image registration in brain mapping. Image. Vis. Comp., 19:3-24.
166. van den Elsen, P., Pol, E.J., and Viergever, M. 1993. Medical image matching - a review with classification. IEEE Eng. Med. Biol., 12:26-39.
167. van Essen, D. 1997. A tension-based theory of morphologenesis and compact wiring in the central nervous system. Nature, 285:313-318.
168. Vatsa, V. and Wedan, B. 1990. Development of a multigrid code for 3-D Navier-Stokes equations and its application to a grid-refinement study. Comp. Fluids., 18:391-403.
169. Viergever, M., Maintz, J., and Stokking, R. 1997. Integration of functional and anatomical brain images. Biophys. Chem., 68:207-219.
170. Viola, P. and Wells, W. 1993. Alignment by maximization of mutual information - a review with classification. 5th Int. Conf. Comp. Vis., IEEE, 5:16-23.
171. Viola, P. and Wells, W: 1997. Alignment by maximization of mutual information. Int. J. Comp. Vision., 24:137-154.
172. Ware, R. and LoPresti, V. 1975. Three-Dimensional reconstruction from serial sections. Int. Rev. Cytol., 40:325-440.
173. Watanabe, H., Andersen, F., Simonsen, C., Evans, S., Gjedde, A., and Cumming, P. 2001. MR-based statistical atlas of the Gottingen minipig brain. Neuroimage, 14:1089-1096.
174. Webster, R. 1994. An algebraic multigrid solver for Navier-Stokes problems. Int. J. Num. Meth. Fluids., 18:761-780.
175. West, J., Fitzpatrick, J., Toms, S., Maurer, C., and Maciunas, R. 2001. Fiducial point placement and the accuracy of point-based, rigid body registration. Neumsurgery, 48:810-817.
176. White, E. 1989, Cortical Circuits. Synoptic Organization of the Cerebral Cortex. Structure, Function, and Theory. Birkhäuser, Boston.
177. Widrow, B. 1973. The rubber-mask technique. I. Pattern Measurement and analysis. Pat. Recog., 5:175-197.
178. Woods, R. 2002. AIR 5.08. http://bishopw.loni.ucla.edu/ AIR5/index.html.
179. Woods, R., Dapretto, M., Sicotte, N., Toga, A., and Mazziotta, J. 1999. Creation and use of a Talairach-compatible atlas for accurate, automated, nonlinear intersubject registration, and analysis of functional imaging data. Hum. Brain. Mapp., 8:73-79.
180. Woods, R., Grafton, S., Holmes, C., Cherry, S., and Mazziotta, J. 1998a. Automated image registration: 1. General methods and intrasubject, intramodality validation. J. Comput. Assist. Tomogr., 22:139-152.
181. Woods, R., Grafton, S., Watson, J., Sicotte, N., and Mazziotta, J. 1998b. Automated image registration: 11. Intersubject validation of linear and nonlinear models. J. Comput. Assist. Tomogr., 22:153-165.
182. Yeshurun, Y. and Schwartz, E. 1999. Cortical hypercolumn size determines stereo fusion limits. Biol. Cyber., 80:117-129.
183. You, J. 1995. Efficient image matching: A hierarchical chamfer matching scheme via distributed system. Real-time. Imag., 1:245-259.
184. Young, M. 1992. Objective analysis of the topological organization of the primate cortical visual system. Nature, 358:152-155.
185. Young, M. 1996, The Analysis of Cortical Connectivity. Springer.
186. Zeiss: 1992. KS400 Reference Guide. Zeiss Vision: Jena.
187. Zhao, W., Young, T., and Ginsberg, M. 1993. Registration and three-dimensional reconstruction of autoradiographic images by the disparity analysis method. IEEE Trans. Med. Imag., 12:782-791.
188. Zhu, Y. 2002. Volume image registration by cross-entropy optimization. IEEE Trans. Med. Imaging., 21:174-180.