Survey of Medical Image Registration

V.R.S Mani^, and Dr. S. Arivazhagan

Cite this paper:
V.R.S Mani and Dr. S. Arivazhagan. Survey of Medical Image Registration. Journal of Biomedical Engineering and Technology. 2013; 1(2):8-25. doi: 10.12691/jbet-1-2-1

Abstract

Computerized Image Registration approaches can offer automatic and accurate image alignments without extensive user involvement and provide tools for visualizing combined images. The aim of this survey is to present a review of publications related to Medical Image Registration. This paper paints a comprehensive picture of image registration methods and their applications. This paper is an introduction for those new to the field, an overview for those working in the field and a reference for those searching for literature on a specific application. Methods are classified according to the different aspects of Medical Image Registration.

Keywords:
image registration deformable model multimodal extrinsic elastic rigid non rigid voxel based feature based

This work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References:

[1]	Hill DLG, Batchelor PG, Holden M, Hawkes DJ. “Medical image registration”. Phys Med Biol 2001; 46:R1-R45.
[2]	Hajnal JV, Hill DLG, Hawkes DJ, editors. In: “Medical image registration”. CRC Press Boca Raton, 2001.
[3]	Pelizzari CA, Chen GTY, Spelbring DR, Weichselbaum RR, Chen C.T. “Accurate 3-dimensional registration of CT, PET, and/or MR images of the brain”. J Computer Assist Tomogr 1989; 13:20-6.
[4]	E. D’Agostino, F. Maesl, D. Vandermeulen, and P. Suetens, “A viscous fluid model for multimodal non-rigid image registration using mutual information,” Med. Image Anal., vol. 7, pp. 565-575, 2003.
[5]	Hawkes DJ, Barratt D, Blackall JM, Chan C, Edwards PJ, Rhode K, et al. “Tissue deformation and shape models in image-guided interventions: a discussion paper”. Med Image Anal 2004.
[6]	Ferrant M, Nabavi A, Macq B, Black PM, Jolesz FA,Kikinis R, et al. “Serial registration of intra operative MR images of the brain”. Med Image Anal 2002; 6:337-59.
[7]	Makela T,Clarysse P, Sipila O,Pauna N, Pham QC , et al.., “A review of cardiac image registration methods”. IEEE Trans Med Imaging 2002; 21:1011-21.
[8]	Hutton BF, Braun M, Thurfjell L, Lau DYH. “Image Registration: an essential tool for nuclear medicine”. EurJ Nucl Med Mol Imaging 2002; 29:559-77.
[9]	Rosenman JG, Miller EP, Tracton G, Cullip TJ. “Image registration: an essential part of radiation therapy treatment Planning”. Int J Radiat Oncol Biol Phys 1998; 40:197-205.
[10]	MeijeringE.H.W,NiessenW.J,ViergeverWA.“Retrospective motion correction in digital subtraction angiography: a review”. IEEE Trans Med Imaging 1999; 18:2-21.
[11]	Toga AW, Thompson PM. “The role of image registration in brain mapping”. Image Vision Comput 2001.
[12]	Thompson PM, Woods RP, Mega MS, Toga AW. “Mathematical/computational challenges in creating deformable and probabilistic atlases of the human brain. Human Brain Mapping” 2000; 9:81-92.
[13]	P.A.van den Elsen,E.J.D.Pol,M.A.Viergever, “Medical Image Matching- A review with classification”,IEEE Eng. in Medicine and Biology., pp. 26-38, March 1993.
[14]	L. Lemieux, N. D. Kitchen, S. W. Hughes and D. G. T. Thomas, “Voxel-based localization in frame-based and frameless stereotaxy and its accuracy”. Medical physics, 21(8):1301-1310, 1994
[15]	K. P. Gall and L. J. Verhey, “Computer-assisted positioning of radiotherapy patients using implanted radio opaque fiducials”, Medical physics, 1993, 1152-1159.
[16]	C. Evans, S. Marrett, J. Torrescorzo, S. Ku, and L.Collins, “MRI-PET correlation in three dimensions using a volume of interest (VOI) atlas”, Journal of cerebral blood flow and metabolism , 11, A69-A78, 1991.
[17]	Simon, D. A., O’Toole, R. V., Blackwell, M., Morgan, F., DiGioia, A. M., and Kanade, T. (1995b). “Accuracy validation in image guided orthopaedic surgery”. In Medical robotics and computer assisted surgery, pp. 185- 192. Wiley.
[18]	Halili Chui, Anand Rangarajan. “A new Point Matching Algorithm for non-rigid Registration” Computer Vision and Image Understanding, 2003, 89:114-141.
[19]	Rohr K, Fornefett M, Stiehl HS.“ Spline-based elastic image registration: integration of landmark errors and orientation attributes”. Comput Vision Image Understanding 2003; 90:153-68.
[20]	Lindeberg T. “Edge detection and ridge detection with automatic scale selection”. Int J Comput Vision 1998; 30:117-54.
[21]	Maintz JBA, vandenElsen PA, Viergever MA.“ Evaluation of ridge seeking operators for multimodality medical image matching”. IEEE Trans Pattern Anal 1996; 18:353-65.
[22]	Subsol G, Roberts N, Doran M, Thirion JP, Whitehouse GH. “Automatic analysis of cerebral atrophy”. Magn Reson Imaging 1997; 15:917-27.
[23]	Chui, H. and Rangarajan, A., “A new point matching algorithm for non rigid registration”, Computer Vision and Image Understanding, Vol. 89,No. 2/3, pp. 114-142, 2003.
[24]	Maurer, C. R., Fitzpatrick, J. M., Galloway, R. L., Wang, M. Y., Maciunas, R. J., and Allen, G. S. (1995). “The accuracy of image-guided neurosurgery using implantable fiducial markers”. In Lemke, H. U., Inamura, K., Jaffe, C. C., and Vannier, M. W.(eds), Computer assisted radiology, pp. 1197-1202, Berlin.Springer-Verlag.
[25]	Davatzikos, C. 1996 “Nonlinear registration of brain images using deformable models”. In Mathematical methods in biomedical image analysis, Los Alamitos, CA. IEEE Computer Society Press. pp. 94-103.1996.
[26]	Thirion, J. 1996. “Non-rigid matching using demons.” In Computer vision and pattern recognition, pp. 245-251, Los Alamitos, CA. IEEE computer society press.
[27]	Chen, C., Pelizzari, C. A., Chen, G. T. Y., Cooper, M. D., and Levin, D. N. “ Image analysis of PET data with the aid of CT and MR images”. In Information processing in medical imaging, pp. 601-611.1987.
[28]	Borgefors, G. (1988). Hierarchical “chamfer matching: a parametric edge matching algorithm”. IEEE Transactions on pattern analysis and machine intelligence, 10, 849-865.
[29]	L. Z¨ollei, A. Yezzi, and T. Kapur. “A variational framework for joint segmentation and registration.” In MMBIA’01: Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis, pages 44-51,Washington, DC, USA, 2001. IEEE Computer Society.
[30]	Y. Chen and L. Wu. “Second order elliptic equations and elliptic systems”, volume 174 of Translations of Mathematical Monographs. American Mathematical Society, Providence, RI, 1998.
[31]	Y. Young and D. Levy. “Registration-based morphing of active contours for segmentation of ct scans”. Mathematical Biosciences and Engineering, 2(1):79-96, 2005.
[32]	K. M. Pohl, J. Fisher, J. J. Levitt, M. E. Shenton, R. Kikinis, W. E. L. Grimson, and W. M. Wells. “A unifying approach to registration, segmentation, and intensity correction”. In 8th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), pages 310-318, 2005.
[33]	M. Droske and W. Ring. “A Mumford -Shah level-set approach for geometric image registration”. SIAM Journal on Applied Mathematics, 66(6):2127-2148, 2006.
[34]	M Droske, W. Ring, and M. Rumpf. “Mumford-Shah based registration: a comparison of a level set and a phase field approach”. Computing and Visualization in Science, 12(3):101-114, 2009.
[35]	Collins DL, LeGoualher G, Venugopal R, Caramanos A, Evans AC, Barillot C. “Cortical constraints for nonlinear cortical registration. Visualization in Biomedical Computing”, Lecture Notes in Computer Science 1996; 1131: 307-16.
[36]	Hellier P, Barillot. C. “Coupling dense and landmark-based approaches for non rigid registration”. IEEE Trans Med Imaging 2003; 22:217-27.
[37]	Liu TM, Shen DG, Davatzikos C. “Deformable registration of cortical structures via hybrid volumetric and surface warping”. Neuro Image 2004; 22:1790-801.
[38]	Thompson PM, MacDonald D, Mega MS, Holmes CJ, Evans AC, Toga AW. “Detection and mapping of abnormal brain structure with a probabilistic atlas of Cortical surfaces”. J Comput Assist Tomogr 1997, 21 567-81.
[39]	Christensen G, Carlson B, Chao KSC, Yin P, Grigsby PW, Nguyen K, et al. “Image-based dose planning of intra cavity branchy therapy: registration of serial imaging studies using deformable anatomic templates”. Int J Radiat Oncol Biol Phys 2001; 51:227-43.
[40]	Russakoff DB, Rohlfing T, Shahidi R, Kim DH, Adler JR, Maurer CR. “Intensity-based 2D-3D spine image registration incorporating one fiducial marker”. Proceedings of MICCAI 2003 Part I, Lecture Notes in Computer Science 2003; 2878:287-94.
[41]	Cachier P, Bardinet E, Dormont D, Pennec X, Ayache.N; Iconic Feature based non rigid registration: the PASHA algorithm”. Computer Vision Image Understanding 2003; 89:272-98.
[42]	Jiangang Liu and Jie Tian Registration of Brain MRI/PET “Images Based on Adaptive Combination of Intensity and Gradient Field Mutual Information” Copyright © 2007 J. Liu and J. Tian. This is an open access article distributed under the Creative Commons Attribution License.
[43]	S. Ourselin, A. Roche, S. Prima, and N. Ayache, “Block matching: A general framework to improve robustness of rigid registration of medical images,” in Medical Image Computing and Computer-Assisted Intervention,
[44]	Studholme, D. L. G. Hill, and D. J. Hawkes, “Automated 3-D registration of MR and CT images of the head,” Med. Image Anal., vol. 1, no.2, pp. 163-175, 1996.
[45]	Woods RP, Grafton ST, Watson JDG, Sicotte NL, Mazziotta JC. “Automated image registration: Intersubject validation of linear and nonlinear models”. J Computer Assist Tomogr 1998; 22:153-65.
[46]	Maurer, C. R., and Fitzpatrick, J. M., “A review of medical image registration, In: Interactive Image Guided Neurosurgery”, pp. 17-44, American Association of Neurological Surgeons, 1993.
[47]	P. Viola and W.M.Wells III, “Alignment by maximization of mutual information,” in Proc. Int. Conf. Computer Vision, E. Grimson, S. Shafer, A. Blake, and K. Sugihara, Eds. Los Alamitos, CA, 1995, pp. 16-23.
[48]	M. Jenkinson and S. Smith, “A global optimization method for robustaffine registration of brain images,” Med. Image Anal., vol. 5, no. 2, pp. 143-156, 2001.
[49]	M. Holden, E. R. E. Denton, J. M. Jarosz, T. C. S. Cox, C. Studholme, D. J. Hawkes, and D. L. G. Hill, “Detecting small anatomical changes with 3D serial MR subtraction images,” in Medical Imaging: Image Processing, K. M. Hanson, Ed. Bellingham, WA: SPIE, 1999, vol. 3661,pp. 44-55. Proc. SPIE.
[50]	R. Shekhar and V. Zagrodsky, “Mutual information-based rigid and non rigid registration of ultrasound volumes,” IEEE Trans. Med. Imag., vol.21, pp. 9-22, Jan. 2002.
[51]	Smadar Gefen, Nahum Kiryati, Louise Bertrand, Jonathan Nissanov, "Planar-to-Curved-Surface ImageRegistration," cvprw, pp.72, 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06), 2006.
[52]	Bookstein FL. “Principal warps - thin-plate splines and the decomposition of deformations”. IEEE Trans Pattern Anal 1989; 11:567-85.
[53]	Rueckert D, Sonoda LI, Hayes C, Hill DLG, Leach MO, Hawkes DJ. “Non rigid registration using free-form deformations: application to breast MR images”. IEEE Trans Med Imaging 1999; 18:712-21.
[54]	Holden M, Schnabel JA, Hill DLG. “Quantification of small cerebral ventricular volume changes in treated growth hormone patients using non-rigid registration”. IEEE Trans Med Imaging 2002; 21:1292-301.
[55]	Mattes D, Haynor DR, Vesselle H, Lewellen TK, Eubank W. “PET-CT image registration in the chest using free-form deformations”. IEEE Trans Med Imaging 2003; 22:120-8.
[56]	Frangi AF, Rueckert D, Schnabel JA, Niessen WJ. “Automatic construction of multiple-object three-dimensional statistical shape models application to cardiac modeling”. IEEE Trans Med Imaging 2002; 21:1151-66.
[57]	McLeish K, Hill DLG, Atkinson D, Blackall JM, Razavi R. “A study of the motion and deformation of the heart due to respiration”. IEEE Trans Med Imaging 2002; 21:1142-50.
[58]	Rohlfing T, Maurer CR, O’Dell WG, Zhong JH. “Modeling liver motion and deformation during the respiratory cycle using intensity-based non rigid registration of gated MR images”. Med Phys 2004; 31:427-32.
[59]	Schnabel JA, Tanner C, Castellano-Smith AD, Degenhard A, Leach MO, Hose DR, et al. “Validation of non-rigid registration using finite element methods: application to breast MR images”. IEEE Trans Med Imaging 2003; 22:238-47.
[60]	Tanner C, Schnabel JA, Degenhard A, Castellano-Smith AD, Hayes C, Leach MO, et al. “Validation of volume preserving non-rigid registration: application to contrast enhanced MR-mammography”. Proceedings of MICCAI 2002, Lecture Notes in Computer Science 2002; 2489:307-14.
[61]	C.Broit, “Optimal registration of deformed images,” Ph.D. dissertation, Univ. Penn., Comput. Inform. Sci Philadelphia, PA, 1981.
[62]	R. Bajcsy, R. Lieberson, and M. Reivich, “A computerized system for the elastic matching of deformed radiographic images to idealized atlas images,” J. Comput. Assist. Tomogr., vol. 7, no. 4, pp. 618-625, 1983.
[63]	Bajcsy R, Kovacic S. “Multi resolution elastic matching”. Comp Vision Graphics Image Processing 1989; 46:1-21.
[64]	Schormann, T., Henn, S., and Zilles, K., “A new approach to fast elastic alignment with applications to human brains”, In: Visualization in Biomedical Computing, Hohne, K. H. and Kikinis, R., eds., Springer- Verlag, Berlin 1996.
[65]	Rohr K, Stiehl HS, Sprengel R, Beil W, Buzug TM, , et al. “Point-based elastic registration of medical image data using approximating thin-plate splines”. Visualization in Biomedical Computing, Lecture Notes in Computer Science 1996; 1131:297-306.
[66]	A.Butt, R. Acharya, C. Sibata, and K. H. Shi, “Surface matching of multimodality image volumes by a fuzzy elastic registration technique,” Comput. Med. Imag. Graph. vol. 22, no. 1, pp. 13-23, 1998.
[67]	Fornefett, M., Rohr, K., and Stiehl, H. S. “Elastic registration of medical images using radial basis functions with compact support”, In: Proc. Computer Vision and Pattern Recognition (CVPR’99), pp. 402-407, Fort Collins, Co, 1999.
[68]	Kybic, J. and Unser, M., “Multidimensional elastic registration of images using splines”, In: Proceedings of ICIP, Vol. 2, pp. 455-458, 2000.
[69]	Shen, D., Davatzikos, C., Hammer: “Hierarchical attribute matching mechanism for elastic registration”. IEEE transactions on medical imaging Vol.21, 1421-39. Nov. 2002..
[70]	S. Periaswamy and H. Farid. “Elastic registration in the presence of intensity variations”. IEEE Transactions on MedicalImaging, 22(7):865-874, July 2003.
[71]	Rohr K, Cathier P, Waorz S. “Elastic registration of electrophoresis images using intensity information and point landmarks”. Pattern Recognition 2004;37(5):1035-1048.
[72]	Franz A, Carlson IC, Renisch S. “An adaptive irregular grid approach using SIFT features for elastic medical image registration”. Procs BVM 2006; 201-205.
[73]	Gonzalo Vegas-S´anchez-Ferrero, etal “Strain Rate Tensor Estimation in Cine Cardiac MRI Based on Elastic Image Registration”, Laboratory of Image Processing. University of Valladolid. Spain 2008 IEEE.
[74]	Fu-Lai Chung, Member, IEEE, Zhaohong Deng, And Shitong Wang “An Adaptive Fuzzy-Inference-Rule-Based Flexible Model For Automatic Elastic Image Registration” IEEE Transactions On Fuzzy Systems, Vol. 17, No. 5, October 2009.
[75]	D. L. Collins and A. C. Evans, “Animal: Validation and applications of nonlinear registration-based segmentation,” Int. J. Pattern Recogn. Artif. Intell., vol. 11, no. 8, pp. 1271-1294, 1997.
[76]	Moulin, R. Krishnamurthy, and J. Woods, “Multiscale modeling and estimation of motion fields for video coding,” IEEE Trans. Image Processing, vol. 6, pp. 1606-1620, Dec. 1997.
[77]	R. Szeliski and H.-Y. Shum, “Motion estimation with quadtree splines,”IEEE Trans. Pattern Anal. Machine Intell., vol. 18, pp. 1199-1207, Dec.1996.
[78]	Musse, F. Heitz, and J.-P. Armspach, “Topology preserving deformable image matching using constrained hierarchical parametric models,” IEEE Trans. Med. Imag., vol. 10, pp. 1081-1093, July 2001.
[79]	Yoshida, “Removal of normal anatomic structures in radiographs using wavelet-based non-linear variational method for image matching,” Wavelet Applicat. Signal Image Process, vol. 3458, pp. 174-181, 1998.
[80]	Kybic, J. and Unser, M, “Fast Parametric Elastic Image Registration” IEEE transactions on image processing, vol. 12, 11,Nov. 2003.
[81]	Christensen GE, Rabbitt RD, Miller MI. “Deformable templates using large deformation kinematics”. IEEE Trans Image Processing 1996; 5:1435-47.
[82]	Lester H, Arridge SR. “A survey of hierarchical non-linear medical image registration”. Pattern Recognition 1999; 32:129-49.
[83]	BroNielsen M, Gramkow C. “Fast fluid registration of medical images. Visualization in Biomedical Computing”, Lecture Notes in Computer Science 1996; 1131:267-76.
[84]	Thirion J-P. “Image matching as a diffusion process: an analogy with Maxwell’s demons”. Med Image Anal 1998; 2:243-60.
[85]	M. F. Beg, M. I. Miller, A. Trouve, and L. Younes, “Computing large deformation metric mappings via geodesic flows of diffeomorphisms,” Int. J. Comput. Vis., vol. 61 (2), pp. 139-157, 2005.
[86]	Glaunès J-A, Trouvé A, Younes L, “Diffeomorphic matching of distributions: a new approach for unlabelled point-sets and sub-manifolds matching”, In proc of the CVPR, 712-718, 2004.
[87]	Ashburner, “A fast diffeomorphic image registration algorithm,” Neuroimage, vol. 38(1), pp. 95 - 113, 2007.
[88]	Miller, M.I., Beg, M.F., Ceritoglu, C., Stark, C.E.L., 2005. Increasing the power of functional maps of the medial temporal lobe using large deformation metric mapping. Proc. Natl. Acad. Sci. U. S. A. 102, 9685-9690.
[89]	L. Younes, “Jacobi fields in groups of diffeomorphisms and applications,” Quart. Appl. Math., vol. 65, pp. 113 - 134, 2007.
[90]	M. Hernandez, M. N. Bossa, and S. Olmos, “Registration of anatomical images using geodesic paths of diffeomorphisms parameterized with stationary vector fields,” IEEE workshop on Math. Meth.in Biomed. Image Anal. (MMBIA 07), 2007.
[91]	Avants, B. B., Epstein, C. L., Grossman, M., Gee, J. C., 2008. “Symmetric diffeomorphic image registration with cross-correlation: Evaluating automated labeling of elderly and neurodegenerative brain”. Medical Image Analysis 12, 26-41.
[92]	Rueckert, D., Aljabar, P., Heckemann, R. A., Hajnal, J. V., Hammers, A., 2006.“Diffeomorphic registration using B-splines”. 9th International Conference on Medical Image Computing and Computer-Assisted Intervention:MICCAI 2006 4191, 702-709.
[93]	M. I. Miga, K. D. Paulsen, J. M. Lemery, S. D. Eisner, A. H. Hartov, F.E. Kennedy, and D. W. Roberts, “Model-updated image guidance: Initial clinical experiences with gravity-induced brain deformation,” IEEE Trans. Med. Imag., vol. 18, pp. 866-874, Oct. 1999.
[94]	M. Ferrant, S. K. Warfield, A. Nabavi, F. A. Jolesz, and R. Kikinis, “Registration of 3D intraoperative MR images of the brain using a finite element biomechanical model,” in Lecture Notes in Computer Science.Berlin, Germany: Springer-Verlag, 2000, vol. 1935, Proc Medical Image Computing and Computer-Assisted Intervention, pp. 19-28.
[95]	O.Skrinjar, C.Studholme, A. Navabi, and J. Duncan, “Steps toward a stereo camera-guided biomechanical model for brain shift compensation,” in Lecture Notes in Computer Science. Berlin, Germany: Springer-Verlag, 2001, vol. 2082, Proc. Information Processing in Medical Imaging, pp. 183-189.
[96]	A.Hagemann, K. Rohr, H. S. Stiehl, U. Spetzger, and J. M. Gilsbach, “Biomechanical modeling of the human head for physically based, nonrigid image registration,” IEEE Trans. Med. Imag., vol. 18, pp. 875-884, Oct. 1999.
[97]	Castellano-Smith, T. Hartkens, J. Schnabel, R. Hose, H. Liu, W. A. Hall, C. L. Truwit, D. J. Hawkes, and D. L. G. Hill, “Constructing patient specific models for correcting intraoperative brain deformation,” in Lecture Notes in Computer Science. Berlin, Germany: Springer-Verlag, 2001, vol. 2208, Proc. Medical Image Computing and Computer-Assisted Intervention, pp. 1091-1098.
[98]	F. S. Azar, D. N. Metaxas, and M. D. Schall, “A finite model of the breast for predicting mechanical deformations during biopsy procedure,” in Proc. IEEE Workshop Mathematical Methods in Biomedical Image Analysis, 2000, pp. 38-45.
[99]	A. Samani, J. Bishop, M. J. Yaffe, and D. B. Plewes, “Biomechanical 3-D finite element modeling of the human breast using MRI data,” IEEE Trans. Med. Imag., vol. 20, pp. 271-279, Apr. 2000.
[100]	R. Sinkus, J. Lorenzen, D. Schrader, M. Lorenzen, M. Dargatz, and D. Holz, “High-resolution tensor MR elastography for breast tumor detection,” Phys. Med. Biol., vol. 45, pp. 1649-1664, 2000.
[101]	D. B. Plewes, J. Bishop, A. Samani, and J. Sciaretta, “Visualization and quantification of breast cancer biomechanical properties with magnetic resonance elastography,” Phys. Med. Biol., vol. 45, pp. 1591-1610, 2000.
[102]	M. M. Doyley, P. M. Meaney, and J. C. Bamber, “Evaluation of an iterative reconstruction method for quantitative elastography,” Phys. Med. Biol., vol. 45, pp.1521-1539, 2000.
[103]	M. I. Miga, “A new approach to elasto graphic imaging: Modality independent elastography,” in Proc. Medical Imaging 2002: Image Processing, vol. 4684, 2002, pp. 604-611.
[104]	Meyer, C. R., Leichtman, G. S., Brunberg, J. A., Wahl, R. L.,and Quint, L. E. (1995). “Simultaneous usage of homologous points, lines, and planes for optimal, 3-D, linear registration of multimodality imaging data”. IEEE Transactions on medical imaging, 14(1), 1-11.
[105]	Maes, F., Collignon, A., Vandermeulen, D., Marchal, G., and Suetens, P. (1996). “Multi-modality image registration by maximization of mutual information”. In Mathematical methods in biomedical image analysis, pp. 14-22, Los Alamitos, CA. IEEE computer society press.
[106]	F. Maes, D. Vandermeulen, and P. Suetens, “Comparative evaluation of multiresolution optimization strategies for multimodality image registrationby maximization of mutual information,” Med. Image Anal.,vol. 3, pp. 373-386, 1999.
[107]	P. W. Pluim, J. B. A. Maintz, and M. A. Viergever, “Mutual information matching in multiresolution contexts,” Image Vis. Computing, vol. 19, pp. 45-52, 2001.
[108]	P. Thevenaz and M. Unser, “Optimization of mutual information for multiresolution image registration,” IEEE Trans. Imag. Process. vol. 9, no. 12, pp. 2083-2099, Dec. 2000.
[109]	Jan Kybic, and Michael Unser, “Fast Parametric Elastic Image Registration”, IEEE Transactions On Image Processing, Vol. 12, No. 11, November 2003, pp1427-1443.
[110]	S. Klein, M. Staring, J.P.W. Pluim. “Evaluation of optimization methods for nonrigid medical image registration using mutual information and B-splines”. IEEE Transactions on Image Processing, 16(12):2879-2890, 2007.
[111]	Mark P. Wachowiak, , Renata Smolíková, , Yufeng Zheng, Jacek M. Zurada, and Adel S. Elmaghraby, “An Approach to Multimodal Biomedical Image Registration Utilizing Particle Swarm Optimization”. IEEE Transactions On Evolutionary Computation, Vol. 8, No. 3, June 2004, pp, 289-301.
[112]	Wang Anna, Wang Tingjun, Zhang Jinjin, Xue Silin “A Novel Method of Medical Image Registration Based on DTCWT and NPSO”. 2009 Fifth International Conference on Natural Computation pp 23-27.
[113]	Penney, G.P., Edwards, P.J., Hipwell, J.H., Slomczykowski, M., Revie, I., Hawkes, D.J., 2007. “Postoperative calculation of acetabular cup position using 2-D-3-Dregistration”. IEEE Trans. Biomed. Eng. 54 (7), 1342-1348.
[114]	Jolesz, F.A., 2005. “Future perspectives for intraoperative MRI”. Neurosurg. Clin. N. Am. 16 (1), 201-213.
[115]	Roth, M., Brack, C., Burgkart, R., Czopf, A., 1999. “Multi-view contourless registration of bone structures using a single calibrated X-ray fluoroscope”. In: Lemke, H.U., Vannier, Inamura, K., Farman, A.G. (Eds.), CARS 1999: Computer Assisted Radiology and Surgery. Proceedings of the 13th International Congress and Exhibition, International Congress Series, vol. 1191. Elsevier, Paris, France, p. 756-761.
[116]	Sadowsky, O., Ramamurthi, K., Ellingsen, L., Chintalapani, G., Prince, J., Taylor, R., 2006. “Atlas-assisted tomography: registration of a deformable atlas to compensate for limited-angle cone-beam trajectory”. In: Third IEEE International Symposium on Biomedical Imaging: Nano to Macro, ISBI2006.IEEE Computer Society Press, pp. 1244-1247.
[117]	Hermans, J., Claes, P., Bellemans, J., Vandermeulen, D., Suetens, P., 2007b. “A robust optimization strategy for intensity-based 2D/3D registration of knee implant models to single-plane fluoroscopy”. In: Pluim, J.P.W., Reinhardt, J.M. (Eds.), Medical Imaging 2007: Image Processing, vol. 6512. SPIE, San Diego, CA, USA, p. 651227.
[118]	Jomier, J., Bullitt, E., Van Horn, M., Pathak, C., Aylward, S.R., 2006. “3D/2D model-to image registration applied to hip surgery”. In: Larsen, R., Nielsen, M., Sporring, J. (Eds.), Ninth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2006), Part 2, Lecture Notes In Computer Science, vol. 4191. Springer, Copenhagen, Denmark, pp. 662-669.
[119]	Zheng, G.Y., Ballester, M.A.G., Styner, M., Nolte, L.P., 2006a. “Reconstruction of patient-specific 3D bone surface from 2D calibrated fluoroscopic images and point distribution model”. In: Larsen, R., Nielsen, M., Sporring, J. (Eds.), Ninth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2006), Part 1, Lecture Notes In Computer Science, vol. 4190. Springer, Copenhagen, Denmark, pp. 25-32
[120]	Zikic, D., Groher, M., Khamene, A., Navab, N., 2008. “Deformable registration of 3D vessel structures to a single projection image”. In: Reinhardt, J.M., Pluim, J.P.W. (Eds.), Medical Imaging 2008: Image Processing, vol. 6914. SPIE, San Diego, CA, USA, p. 6914-6916.
[121]	Chan, H.M., Chung, A.C.S., Yu, S., Wells, W.M.I.I.I., 2004. “2D-3D vascular registration between digital subtraction angiographic (DSA) and magnetic resonance angiographic (MRA) images”. In: IEEE International Symposium on Biomedical Imaging: Nano to Macro, vol. 1, pp. 708-711.
[122]	Hipwell, J.H., Penney, G.P., McLaughlin, R.A., Rhode, K., Summers, P., Cox, T.C., Byrne,J.V., Noble, J.A., Hawkes, D.J., 2003. “Intensity-based 2-D-3-D registration of cerebral angiograms”. IEEE Trans. Med. Imag. 22 (11), 1417-1426.
[123]	Turgeon, G.A., Lehmann, G., Guiraudon, G., Drangova, M., Holdsworth, D., Peters, T., 2005. “2D-3D registration of coronary angiograms for cardiac procedure planning and guidance”. Med. Phys. 32 (12), 3737-3749.
[124]	D. Mattes, D. R. Haynor, H. Vesselle, T. K. Lewellen, and W. Eubank, “PET-CT image registration in the chest using free-form deformations,” IEEE Trans. Med. Imag., vol. 22, no. 1, pp. 120-128, Jan. 2003.
[125]	Juan du, Songyuan tang, Tianzi Jiang and Zhensu lu “Intensity-based robust similarity for multimodal image registration” International Journal of Computer Mathematics Vol. 83, No. 1, January 2006, 49-57.
[126]	Alexander Wong, William Bishop,. “Indirect Knowledge-Based Approach to Non-Rigid Multi-Modal Registration of Medical Images”,2007 IEEE, pp 1175-1178.
[127]	Gueziec, A., Kazanzides, P., Williamson, B., Taylor, R.H., 1998. “Anatomy-based registration of CT-scan and intraoperative X-ray images for guiding a surgical robot”. IEEE Trans. Med. Imag. 17 (5), 715-728.
[128]	Prümmer, M., Hornegger, J., Pfister, M., Dörfler, A., “Multi-modal 2D-3D non rigid registration”. In: Reinhardt, J., Pluim, J. (Eds.), Medical Imaging 2006: Image Processing, vol. 6144. SPIE, San Diego CA, USA, p. 61440X.
[129]	Penney, G.P., Batchelor, P.G., Hill, D.L.G., Hawkes, D.J., Weese, J., 2001. “Validation of a two- to three-dimensional registration algorithm for aligning preoperative CT images and intraoperative fluoroscopy images.” Med. Phys. 28 (6), 1024-1032.
[130]	Rhode, K.S., Hill, D.L.G., Edwards, P.J., Hipwell, J., Rueckert, D., Sanchez-Ortiz, G.,Hegde, S., Rahunathan, V., Razavi, R., 2003. “Registration and tracking to integrate X-ray and MR images in an XMR facility”. IEEE Trans. Med. Imag. 22 (11), 1369-1378.
[131]	Rohlfing, T., Maurer, C., 2002. “A novel image similarity measure for registration of 3-D MR images and X-ray projection images”. In: Dohi, T., Kikinis, R. (Eds.), Fifth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2002), Lecture Notes in Computer Science, vol. 2489. Springer, Tokio, Japan, pp. 469-476.
[132]	Sundar, H., Khamene, A., Xu, C., Sauer, F., Davatzikos, C., 2006. “A novel 2D-3D registration algorithm for aligning fluoro images with 3D pre-op CT/MR images”. Medical Imaging 2006: Visualization, Image-Guided Procedures, and Display, vol. 6141. SPIE, San Diego, CA, USA, p. 61412K.
[133]	J.V. Hajnal, N. Saeed, A. Oatridge, E.J. Willimas, I.R. Young, and G.M. Bydder, “Detection of subtle brain changes using subvoxel registration and subtraction of serial MR images”. J. Comp. Assist. Tomogr. vol. 19, pp. 677-691, 1995.
[134]	F.J.S. Castro, C. Pollo, R. Meuli, P. Maeder, O. Cuisenaire, M.B. Cuadra, J.-G. Villemure and J.-P. Thiran, “A Cross Validation Study of Deep Brain Stimulation Targeting: From Experts to Atlas-Based, Segmentation-Based and Automatic Registration Algorithms,” IEEE Transactions on Medical Imaging, vol. 25, 1440-50, 2006.
[135]	G. Eggers, J. Mühling, R. Marmulla “Image-to-patient registration techniques in head surgery” International Journal of Oral and Maxillofacial Surgery, Volume 35, Issue 12, December 2006, Pages1081-1095.
[136]	Almaveh.A,Moseley,J,HunterS.M,ChauL,Breen.S,Brock.K. “Bio-Mechanical based Image Registration for Head and Neck Radiation Treatment”. Phys Med Biol. 2010 Nov 7;55(21).
[137]	Choonik Lee, Katja M. Langen, Weiguo Lu, Jason Haimerl, Eric Schnarr, Kenneth J. Ruchala, Gustavo H. Olivera, Sanford L. Meeks, Patrick A. Kupelian, Thomas D. Shellenberger, Rafael R. Maño “Evaluation of geometric changes of parotid glands during head and neck cancer radiotherapy using daily MVCT and automatic deformable registration”, Radiotherapy and Oncology, Volume 89, Issue 1, October 2008, Pages81-88.
[138]	Ching-Fen Jiang, Ti-Cheng Lu, Shuh-Ping “Interactive image registration tool for positioning verification in head and neck radiotherapy” Computers in Biology and Medicine, Volume 38, Issue 1, January 2008, Pages 90-100.
[139]	Suzanne van Beek, Simon van Kranen, Angelo Mencarelli, Peter Remeijer, Coen Rasch, Marcel van Herk, Jan-Jakob Sonke “First clinical experience with a multiple region of interest registration and correction method in radiotherapy of head-and-neck cancer patients” Radiotherapy and Oncology, Volume 94, Issue 2, February 2010, Pages 213-217.
[140]	Rob H. Ireland, Karen E. Dyker, David C. Barber, Steven M. Wood, Michael B. Hanney, Wendy B. Tindale, Neil Woodhouse, Nigel Hoggard, John Conway, Martin H. Robinson “Non rigid Image Registration for Head and Neck Cancer Radiotherapy Treatment Planning With PET/CT” International Journal of Radiation Oncology*Biology*Physics, Volume 68, Issue 3, 1 July 2007, Pages 952-957.
[141]	Pierre Castadot, John Aldo Lee, Adriane Parraga, Xavier Geets, Benoît Macq, Vincent Grégoire “Comparison of 12 deformable registration strategies in adaptive radiation therapy for the treatment of head and neck tumors” Radiotherapy and Oncology, Volume 89, Issue 1, October 2008, Pages 1-12.
[142]	T. Hartkens, D. L. G. Hill*, A. D. Castellano-Smith, D. J. Hawkes, C. R. Maurer, Jr., A. J. Martin, W. A. Hall, H. Liu, and C. L. Truwit “Measurement and Analysis of Brain Deformation During Neurosurgery IEEE transactions on Medical Imaging”, vol. 22, no. 1, January 2003 pp,82-92.
[143]	A.Gholipour, N. Kehtarnavaz, R. Briggs, M. Devous, and K. Gopinath, “Brain functional localization: A survey of image registration techniques,” IEEE Trans. Med. Imag., vol. 26, no. 4, pp. 427-451, Apr. 2007.
[144]	Ali Gholipour, Nasser Kehtarnavaz, , Kaundinya Gopinath, and Richard Briggs, “Cross-Validation of Deformable Registration With Field Maps in Functional Magnetic Resonance Brain Imaging”, IEEE Journal Of Selected Topics In Signal Processing, Vol. 2, No. 6, December 2008 Pp854-869.
[145]	Crum, W. R., Rueckert, D., Jenkinson, M., Kennedy, D., Smith, S. M., 2004. “A framework for detailed objective comparison of non-rigid registration algorithms in neuro imaging”. Medical Image Computing and Computer- Assisted Intervention: MICCAI 2004 3216, 679-686.
[146]	Hellier, P., Barillot, C., Corouge, I., Gibaud, B., Goualher, G. L., Collins, D. L., Evans, A., Malandain, G., Ayache, N., Christensen, G. E., Johnson, H. J., Sep. 2003. “Retrospective evaluation of inter subject brain registration”. IEEE transactions on medical imaging 22, 1120-30.
[147]	Robbins, S., Evans, A. C., Collins, D. L., Whitesides, S., Sep. 2004. “Tuning and comparing spatial normalization methods”. Medical Image Analysis 8, 311-323., Sep. 2004
[148]	Yassa, M. A., Stark, C. E. L., 2009. “A quantitative evaluation of cross participant registration techniques for MRI studies of the medial temporal lobe”. Neuro Image 44, 319-327.
[149]	Ardekani, B. A., Guckemus, S., Bachman, A., Hoptman, M. J., Wojtaszek, M., Nierenberg, J., Mar. 2005. “Quantitative comparison of algorithms for inter-subject registration of 3D volumetric brain MRI scans”. Journal of Neuroscience Methods 142, 67-76.
[150]	V. A. Magnotta, H. J. Bockholt, H. J. Johnson, G. E. Christensen, and N. C. Andreasen, “Sub cortical, cerebellar, and magnetic resonance based consistent brain image registration,” NeuroImage, vol. 19, pp. 233-245, 2003.
[151]	Jiangang Liu and Jie Tian “Registration of Brain MRI/PET Images Based on Adaptive Combination of Intensity and Gradient Field Mutual Information” Hindawi Publishing Corporation International Journal of Biomedical Imaging Volume 2007, Article ID 93479.
[152]	Bin Fang and Yuan Yan Tang, “Elastic Registration for Retinal Images Based on Reconstructed Vascular Trees”, IEEE Transactions On Biomedical Engineering, Vol. 53, No. 6, June 2006, pp 1183-1187.
[153]	Thitiporn Chanwimaluang, Guoliang Fan, and Stephen R. Fransen, “ Hybrid Retinal Image Registration”, IEEE Transactions On Information Technology In Biomedicine, Vol. 10, No. 1, January 2006,pp 129-142.
[154]	V. Stewart, C.-L. Tsai, and B. Roysam, “The dual-bootstrap iterative closest point algorithm with application to retinal image registration,” IEEE Trans. Med. Imag., vol. 22, no. 11, pp. 1379-1394, Nov. 2003.
[155]	G. K. Matsopoulos, N. A. Mouravliansky, K. K. Delibasis, and K.S. Nikita, “Automatic retinal image registration scheme using global optimization techniques,” IEEE Trans. Inf. Technol. Biomed., vol. 3, no. 1, pp. 47-60, Mar. 1999.
[156]	Jian Zheng; Jie Tian; Kexin Deng; Xiaoqian Dai; Xing Zhang; Min Xu’; “Salient Feature Region: A New Method for Retinal Image Registration,” IEEE Transactions on Information Technology in Biomedicine, Volume: 15 Issue:2 pp 221 - 232.
[157]	W. Jacquet, E. Nyssen, P. Bottenberg, B. Truyen, P. de Groen “2D image registration using focused mutual information for application in dentistry” Computers in Biology and Medicine, Volume 39, Issue 6, June 2009, Pages 545-553.
[158]	Heinz-Theo Luebbers, Peter Messmer, Joachim Anton Obwegeser, Roger Arthur Zwahlen, Ron Kikinis, Klaus Wilhelm Graetz “Comparison of different registration methods for surgical navigation in cranio-maxillofacial surgery” Journal of Cranio-Maxillofacial Surgery, Volume 36, Issue 2, March 2008, Pages 109-116.
[159]	Vasiliki E. Markaki, Pantelis A. Asvestas, George K. Matsopoulos “An iterative point correspondence algorithm for automatic image registration: An application to dental subtraction radiography” Computer Methods and Programs in Biomedicine, Volume 93, Issue 1, January 2009, Pages 61-72.
[160]	Won-Jin Yi, Min-Suk Heo, Sam-Sun Lee, Soon-Chul Choi, Sun-Bok Lee, Kyung-Hoe Huh “Automatic noise robust registration of radiographs for subtraction using strategic local correlation: an application to radiographs of dental implants” Computers in Biology and Medicine, Volume 35, Issue 3, March 2005, Pages 247-258.
[161]	Diaa Eldin M. Nassar, Hany H. Ammar “A neural network system for matching dental radiographs” Pattern Recognition, Volume 40, Issue 1, January 2007, Pages 65-79.
[162]	Georg Eggers, Joachim Mühling, Rüdiger Marmulla “Template-Based Registration for Image-Guided Maxillofacial Surgery” Journal of Oral and Maxillofacial Surgery, Volume 63, Issue 9, September 2005, Pages 1330-1336.
[163]	Omaima Nomir, Mohamed Abdel-Mottaleb “Hierarchical contour matching for dental X-ray radiographs” Pattern Recognition, Volume 41, Issue 1, January 2008, Pages 130-138.
[164]	M. Tsuji, N. Noguchi, M. Shigematsu, Y. Yamashita, K. Ihara, M. Shikimori, M. Goto “A new navigation system based on cephalograms and dental casts for oral and maxillofacial surgery” International Journal of Oral and Maxillofacial Surgery, Volume 35, Issue 9, September 2006, Pages 828-836.
[165]	Yu-Chih Chiang, Reinhard Hickel, Chun-Pin Lin, Karl-Heinz Kunzelmann “Shrinkage vector determination of dental composite by μ CT images” Composites Science and Technology, Volume 70, Issue 6, June 010, Pages 989-994.
[166]	Piotr J. Slomka, Ph.D; Damini Dey, Ph.D; Christian Przetak, MD; Usaf E. Aladl, Ph.D; and Richard P. Baum, MD “Automated 3-Dimensional Registration of Stand- Alone 18F-FDG Whole-Body PET with CT” Journal of Nuclear Medicine • Vol. 44 • No. 7 . July 2003.Pages 1156-1167.
[167]	Matsopoulos GK, Mouravliansky NA, Asvestas PA, Delibasis KK, Kouloulias V. “Thoracic non-rigid registration combining self-organizing maps and radial basis functions”. Med Image Anal. 2005; 9(3):237-54.
[168]	Silva JS, Cancela J, Teixeira L. “Intra-patient registration methods for thoracic CT exams”. Proceedings of the Second International Conference on Bio-inspired System and Signal Processing; 2009; Porto, Portugal. BIOSTEC; 2009:285-90.
[169]	Thomas Köhler, Tobias Klinder, Udo van Stevendaal, Cristian Lorenz, Peter Forthmann “Correction of Breathing Motion in the Thorax for Helical CT”, Tsinghua Science & Technology, Volume 15, Issue 1, February 2010, Pages 87-95.
[170]	Moreno A, Chambon S, P Santhanam A, P Rolland J, Angelini E, Bloch I. “Combining a breathing model and tumor-specific rigidity constraints for registration of CT-PET thoracic data”. Comput Aided Surg. 2008; 13(5):281-98.
[171]	Krol, A., Coman, I. L., Mandel, J. A., Baum, K. G., Luo, M., Feiglin, D. H., Lipson, E. D., Beaumont, J., “Inter-Modality Non-Rigid Breast Image Registration Using Finite-Element Method,” Nuclear Science Symposium Conference Record, IEEE, 3, pp. 1958-1961, 2003.
[172]	Krol, A., Unlu, M. Z., Baum, K. G., Mandel, J. A., Lee, W., Coman, I. L., Lipson, E. D., Feiglin, D. H., “MRI/PET Nonrigid Breast-Image Registration Using Skin Fiducial Markers,” Physica Medica European Journal of Medical Physics, XXI, Supplement 1, pp. 31-35, 2006.
[173]	Krol, A., Unlu, M. Z., Magri, A., Lipson, E., Coman, I. L., Mandel, J. A., Baum, K. G., Feiglin, D. H., “Iterative Finite Element Deformable Model For Nonrigid Coregistration of Multimodal Breast Images,” Biomedical Imaging: Macro to Nano, IEEE International Symposium, pp. 852-855, 2006.
[174]	Baum, K.G., “Multimodal Breast Imaging: Registration, Visualization, and Image Synthesis,” PhD Dissertation, Rochester Institute of Technology, Chester F. Carlson Center for Imaging Science, 2008.
[175]	Ioana L. Coman , Andrzej Krol, James A., Mandel , Karl G. Baum , Min Luo , Edward D. Lipson , David H.Feiglin “Finite-element method for inter modality non rigid breast registration using external skin markers” Medical Imaging 2004: Image Processing, edited by J. Michael Fitzpatrick, Milan Sonka, Proceedings of SPIE Vol. 5370 (SPIE, Bellingham, WA,),pp 1152 - 1155.
[176]	Mainardi, K. M. Passera, A. Lucesoli, D. Vergnaghi, G. Trecate, E. Setti, R. Musumeci, and S. Cerutti , “A Nonrigid Registration of MR Breast Images Using Complex-valued Wavelet Transform” Journal of Digital Imaging, Vol 21, No 1 (March), 2008: pp 27-36.
[177]	Xiao GF, Brady JM, Noble JA, Burcher M, English R. “Non rigid registration of 3-D free-hand ultrasound images of the breast”. IEEE Trans Med Imaging 2002; 21:405-412.
[178]	G. J. Klein and R. H. Huesman, “Four-dimensional processing of deformable cardiac PET data,” Med. Image Anal., vol. 6, pp. 29-46, 2002.
[179]	Jolanta Misko , Mirosaw Dziuk , Ewa Skrobowska, Norbert Szalus , Jacek Pietrzykowski, Agnieszka Warczynska, “Co-Registration of Cardiac MRI and Rest Gated SPECT in the Assessment of Myocardial Perfusion, Function and Viability” Journal of Cardiovascular Magnetic Resonance, Volume 8, Issue 2 May 2006 , pages 389 - 397.
[180]	M. Bidaut and J.-P. Vallee, “Automated registration of dynamic MRimages for the quantification of myocardial perfusion,” J. Magn. Res. Imag., vol. 13, pp. 648-655, 2001.
[181]	G. J. Klein, B.W. Reutter, and R. H. Huesman, “Four-dimensional affine registration models for respiratory-gated PET,” IEEE Trans. Med. Imag., vol. 48, pp. 756-760, Mar.2002.
[182]	Maria Carla Gilardi, Giovanna Rizzo, Annarita Savi, Claudio Landoni, Valentino Bettinardi, Claudio Rossetti, Giuseppe Striano, Ferruccio Fazio “Correlation of SPECT and PET cardiac images by a surface matching registration technique” Computerized Medical Imaging and Graphics, Volume 22, Issue 5, September-October 1998, Pages 391-398.
[183]	Guetter C,Wacker M, Xu C, et al. “Registration of cardiac SPECT/CT data through weighted intensity co-occurrence priors”. Proc MICCAI. 2007; 4791:725-733.
[184]	Dimitrios Perperidis, Raad H. Mohiaddin, Daniel Rueckert “Spatio-temporal free-form registration of Cardiac MR image sequences” Medical Image Analysis, Volume 9, Issue 5, October 2005, Pages 441-456.
[185]	Jasbir Sra, Shivani Ratnakumar “Cardiac image registration of the left atrium and pulmonary veins” Heart Rhythm, Volume 5, Issue 4, April 2008, Pages 609-617.
[186]	M.J. Ledesma-Carbayo, P. Mahía-Casado, A. Santos, E. Pérez-David, M.A. García-Fernández, M. Desco “Cardiac motion analysis from ultrasound sequences using nonrigid registration: Validation against Doppler tissue velocity” Ultrasound in Medicine & Biology, Volume 32, Issue 4, April 2006, Pages 483-490.
[187]	Hongkai Wang, Jing Bai, Yongxin Zhou, Yonghong Zhang “Atlas mapping in CT and MR volume images using a normalized abdominal coordinate system” Computerized Medical Imaging and Graphics, Volume 32, Issue 6, September 2008, Pages 442-451.
[188]	O. Camara, O. Colliot, I. Bloch “Computational modeling of thoracic and abdominal anatomy using spatial relationships for image segmentation” Real-Time Imaging, Volume 10, Issue 4, August 2004,Pages263-273.
[189]	Xishi Huang and Peter C. W. Kim Paul, S. Babyn, Thomas Looi “A novel hybrid model for deformable image registration in abdominal procedure” Proc. SPIE 7964, 79640K (2011); doi:10.1117/12.878068.
[190]	Lausch.A Ebrahimi, M.; Martel, “A registration for abdominal dynamic contrast-enhanced magnetic resonance images” Biomedical Imaging: From Nano to Macro, 2011 IEEE International Symposium pages: 561 - 565.
[191]	Steven F. Petit, Wouter J.C. van Elmpt, Philippe Lambin, André L.A.J. Dekker “Dose recalculation in megavoltage cone-beam CT for treatment evaluation: Removal of cupping and truncation artefacts in scans of the thorax and abdomen”; Radiotherapy and Oncology, Volume 94, Issue 3, March 2010, Pages 359-366.
[192]	Kiefer, T Kuwert, D Hahn, J Hornegger, M Uder, P Rit “Anatomical accuracy of abdominal lesion localization. Retrospective automatic rigid image registration between FDG-PET and MRI”. Nuclear Medicine (2011) Volume: 50, Issue: 4Pages A: 147-154.
[193]	Michael Velec, Joanne L. Moseley, Cynthia L. Eccles, Tim Craig, Michael B. Sharpe, Laura A. Dawson, “Effect of Breathing Motion on Radiotherapy Dose Accumulation in the Abdomen Using Deformable registration” International Journal of Radiation Oncology*Biology*Physics, Volume 80, Issue 1, 1 May 2011, Pages 265-272.
[194]	Thomas Lange, Thomas Wenckebach, Hans Lamecker, Martin Seebaß, Michael Hünerbein, Sebastian Eulenstein, Peter-Michael Schlag “Registration of portal and hepatic venous phase of MR/CT data for computer-assisted liver surgery planning “ International Congress Series, Volume 1281, May 2005, Pages 768-772.
[195]	G.P. Penney, J.M. Blackall, M.S. Hamady, T. Sabharwal, A. Adam, D.J. Hawkes “Registration of freehand 3D ultrasound and magnetic resonance liver images” Medical Image Analysis, Volume 8, Issue 1, March 2004, Pages 81-91.
[196]	He Wang, Sunil Krishnan, Xiaochun Wang, A. Sam Beddar, Tina M. Briere, Christopher H. Crane, Radhe Mohan, Lei Dong “Improving Soft-Tissue Contrast in Four-Dimensional Computed Tomography Images of Liver Cancer Patients Using a Deformable Image Registration Method” International Journal of Radiation Oncology*Biology*Physics, Volume 72, Issue 1, 1 September 2008, Pages 201-209.
[197]	Wen-Chi Christina Lee, Mitchell E. Tublin, Brian E. Chapman “MR and CT images of the liver: comparison of voxel similarity and surface based registration algorithms” Computer Methods and Programs in Biomedicine, Volume 78, Issue 2, May 2005, Pages 101-114.
[198]	Romain, O. Lucidarme, J. Dauguet, S. Mulé, N. Souedet, Y. Chenoune, A. Guibal, T. Delzescaux, F. Frouin “Registration and functional analysis of CT dynamic image sequences for the follow-up of patients with hepatic tumors undergoing anti angiogenic therapy” IRBM, Volume 31, Issues 5-6, October-December 2010, Pages 263-270.
[199]	Haytham Elhawary, Sota Oguro, Kemal Tuncali, Paul R. Morrison, Servet Tatli, Paul B. Shyn, Stuart G. Silverman, Nobuhiko Hata “Multimodality Non-rigid Image Registration for Planning, Targeting and Monitoring During CT-Guided Percutaneous Liver Tumor Cryoablation” Academic Radiology, Volume 17, Issue 11, November 2010, Pages 1334-1344.
[200]	T Böttger, N.V Ruiter, R Stotzka, R Bendl, K.K Herfarth “Registration of CT and MRI volume data of the liver” International Congress Series, Volume 1256, June 2003, Pages 118-123.
[201]	Mahapatra, D.; Ying Sun; “Registration of dynamic renal MR images using neurobiological model of saliency” Biomedical Imaging: From Nano to Macro, 2008. ISBI 2008. 5th IEEE International Symposium page(s):1119 - 1122.
[202]	A.D. Merrem, F. G. Zoellner, and L. R. Schad “A variational approach to image registration in DCE-MRI of human kidney” Proc. Intl. Soc. Mag. Reson. Med. 19 (2011) page 815
[203]	Ong, R.E.; Glisson, C.; Altamar, H.; Viprakasit, D.; Clark, P.; Herrell, S.D.; Galloway, R.L.; “Intra procedural Registration for Image-Guided Kidney Surgery” , IEEE Transactions on Mechatronics,Volume: 15 Issue: 6 Dec. 2010 page(s): 847 - 852.
[204]	Francisco J.Galdames, Claudio A. Perezab, Pablo A. Estévezab, Claudio M. Helda, Fabrice Jailletc, Gabriel Lobod, Gilda Donosod, Claudia Coll “Registration of renal SPECT and 2.5D US image” Computerized Medical Imaging and Graphics Volume 35, Issue 4, Pages 302-314 (June 2011) Bottom of Form.
[205]	Frank G. Zöllner, Rosario Sance, Peter Rogelj, María J. Ledesma-Carbayo, Jarle Rørvik, Andrés Santos, Arvid Lundervold “Assessment of 3D DCE-MRI of the kidneys using non-rigid image registration and segmentation of voxel time courses” Computerized Medical Imaging and Graphics, Volume 33, Issue 3, April 2009, Pages 171-181.
[206]	Ting Song, Vivian S. Lee, Qun Chen, Henry Rusinek, Andrew F. Laine “An automated three-dimensional plus time registration framework for dynamic MR renography” Journal of Visual Communication and Image Representation, Volume 21, Issue 1, January 2010, Pages 1-8.
[207]	Y. Sun, J. M. F. Moura, and C. Ho, “Subpixel registration in renal perfusion MR image sequence”,. in Proc. 2004 IEEEInt. Symp. Biomedical Imaging, Arlington, VA, April 2004.
[208]	Sudhakar Chelikani, Kailasnath Purushothaman, Jonathan Knisely, Zhe Chen, Ravinder Nath, Ravi Bansal, James Duncan “A gradient feature weighted Minimax algorithm for registration of multiple portal images to 3D CT volumes in prostate radiotherapy” International Journal of Radiation Oncology*Biology*Physics, Volume 65, Issue 2, 1 June 2006, Pages 535-547.
[209]	Carlos R. Castro-Pareja, Vladimir Zagrodsky, Lionel Bouchet, Raj Shekhar “Automated prostate localization in external-beam radiotherapy using mutual information-based registration of treatment planning CT and daily 3D ultrasound” International Congress Series, Volume 1281, May 2005, Pages 435-440.
[210]	Baowei Fei, Jeffrey L. Duerk, D. Bruce Sodee, David L. Wilson “Semiautomatic Nonrigid Registration for the Prostate and Pelvic MR Volumes” Academic Radiology, Volume 12, Issue 7, July 2005, Pages 815-824.
[211]	Jennifer M. Hensel, Cynthia Ménard, Peter W.M. Chung, Michael F. Milosevic, Anna Kirilova, Joanne L. Moseley, Masoom A. Haider, Kristy K. BrockDevelopment of Multiorgan “Finite Element-Based Prostate Deformation Model Enabling Registration of Endorectal Coil Magnetic Resonance Imaging for Radiotherapy Planning. International Journal of Radiation Oncology*Biology*Physics, Volume 68, Issue 5, 1 August 2007, Pages1522-1528.
[212]	Chao Lu, Sudhakar Chelikani, Xenophon Papademetris, Jonathan P. Knisely, Michael F. Milosevic, Zhe Chen, David A. Jaffray, Lawrence H. Staib, James S. Duncan “An integrated approach to segmentation and nonrigid registration for application in image-guided pelvic radiotherapy” Medical Image Analysis, Volume 15, Issue 5, Octobeber 2011,Pages772-785.
[213]	He Wang, Lei Dong, Ming Fwu Lii, Andrew L. Lee, Renaud de Crevoisier, Radhe Mohan, James D. Cox, Deborah A. Kuban, Rex Cheung “Implementation and validation of a three-dimensional deformable Registration algorithm for targeted prostate cancer Radio therapy International Journal of Radiation Oncology Biology Physics, Volume 61,Issue3,March 2005,Pages725-735.
[214]	M. Rex Cheung, Karthik Krishnan, “Interactive Deformation Registration of Endorectal Prostate MRI Using ITK Thin Plate Splines” Academic Radiology, Volume 16, Issue 3, March 2009, Pages351-357.
[215]	Hyunjin Park, Morand R. Piert, Asra Khan, Rajal Shah, Hero Hussain, Javed Siddiqui, Thomas L. Chenevert, Charles R. Meyer, “Registration Methodology for Histological Sections and In Vivo Imaging of Human Prostate” Academic Radiology, Volume 15, Issue 8, August 2008, Pages 1027-1039.
[216]	Monique H.P. Smitsmans, Josien de Bois, Jan-Jakob Sonke, Anja Betgen, Lambert J. Zijp, David A. Jaffray, Joos V. Lebesque, Marcel van Herk, “Automatic prostate localization on cone-beam CT scans for high precision image-guided radiotherapy” International Journal of Radiation Oncology Biology Physics, Volume 63, Issue 4, 15 November2005,Pages975-984.
[217]	Joakim H Jonsson,, Patrik Brynolfsson, Anders Garpebring, Mikael Karlsson, Karin Söderström and Tufve Nyholm, “Registration accuracy for MR images of the prostate using a sub volume based registration protocol” Radiation Oncology 2011, 6:73 http://www.ro-journal.com/content/6/1/73.
[218]	Daniel B. Russakoff, Torsten Rohlfing, John R. Adler Jr, Calvin R. Maurer Jr, “Intensity-based 2D-3D spine image registration incorporating a single fiducial marker” Academic Radiology, Volume 12, Issue 1, January 2005, Pages 37-50.
[219]	Andrew Lang, Parvin Mousavi, Sean Gill, Gabor Fichtinger, Purang Abolmaesumi “Multi-modal Registration of speckle-tracked freehand 3D ultrasound to CT in the lumbar spine” Medical Image Analysis, August2011.
[220]	Sean Gill, Purang Abolmaesumi, Gabor Fichtinger, Jonathan Boisvert, David Pichora, Dan Borshneck, Parvin Mousavi “Bio mechanically constrained group wise ultrasound to CT Registration of the lumbar spine,” Medical Image Analysis, August 2010.
[221]	Elias C. Papadopoulos, Federico P. Girardi, Andrew Sama, Harvinder S. Sandhu, Frank P. Cammisa Jr “Accuracy of single-time, multilevel registration in image-guided spinal surgery,” The Spine Journal, Volume 5, Issue 3, May-June 2005,Pages263-267.
[222]	Susanne Winter, Bernhard Brendel, Christian Igel “Registration of bone structures in 3D ultrasound and CT data: Comparison of different optimization strategies,” International Congress Series, Volume 1281, May 2005, Pages 242-247.
[223]	A.Yezzi, L. Zöllei, T. Kapur, “A variational framework for integrating segmentation and registration through active contours,” Medical Image Analysis, Volume 7, Issue 2, June 2003, Pages171-185.
[224]	Miguel Á. Martín-Fernández, Rubén Cárdenes, Emma Muñoz-Moreno, Rodrigo de Luis-García, Marcos Martín-Fernández, Carlos Alberola-López, “Automatic articulated registration of hand radiographs Image and Visio Computing”, Volume 27, Issue 8, 2 July 2009, Pages 1207-1222.
[225]	Janet Golden stein, Joseph Schooler, Jason C. Crane, Eugene Ozhinsky, Jean-Baptist Pialat, Julio Carballido-Gamio, Sharmila Majumdar, “Prospective image registration for automated scan prescription of follow-up knee images in quantitative studies,” Magnetic Resonance Imaging, Volume 29, Issue 5, June 2011, Pages 693-700.
[226]	Janet Blumenfeld, Julio Carballido-Gamio, Roland Krug, Daniel J. Blezek, Ileana Hancu and Sharmila Majumdar, “Automatic Prospective Registration of High-Resolution Trabecular Bone Images of the Tibia” Annals of Biomedical Engineering Volume 35, Number 11, 1924-1931.
[227]	Masaki Takao, Nobuhiko Sugano, Takashi Nishii, Hisahi Tanaka, Jun Masumoto, Hidenobu Miki, Yoshinobu Sato, Shinichi Tamura, Hideki Yoshikawa, “Application of three-dimensional magnetic resonance image registration for monitoring hip joint diseases” Magnetic Resonance Imaging, Volume 23, Issue 5, June 2005, Pages 665-670.
[228]	Youngjun Kim, Kang-Il Kim, Jin hyeok Choi, Kunwoo Lee, “Novel methods for 3D postoperative analysis of total knee arthroplasty using 2D-3D image registration” clinical Biomechanics, Volume 26, Issue 4, May-2011, Pages384-391.
[229]	J.L. Jaremko, R.W.T. Cheng, R.G.W.Lambert, A.F. Habib, J.L. Ronsky, “Reliability of an efficientMRI-based method for estimation of knee cartilage volume using surface registration Osteoarthritis and Cartilage”, Volume 14, Issue 9, September 2006,Pages914-922.