Abstract
In the last few decades, image registration has been established as a very active research area in computer vision. Over the years, image registration applications cover a broad range of real-world problems including remote sensing, medical imaging, artificial vision, and computer-aided design. This chapter deals with the image registration problem, in particular dental image registration using computational intelligence techniques. In the practical applications, there are many medical images needing to be registered at some time and the requirement for the time of the registration is high. Image registration is the process of transforming different sets of data into one coordinate system. Data may be multiple photographs, data from different sensors, from different times, or from different viewpoints. Registration is necessary in order to be able to compare or integrate the data obtained from these different measurements.
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References
Gottesfeld, L.: Survey of image registration techniques. ACM Comput. Surv 24(4), 325–376 (1992)
Damas, S., Cordon, O., Santamaria, J.: Medical image registration using evolutionary computation: an experimental survey. IEEE Comput. Intell. Mag. 6, 26–42 (2011)
Crum, W.R., Hartkens, T., Hill, D.L.: Non-rigid image registration: theory and practice. Br. J. Radiol. 77, 140–153 (2004)
Karsli, F., Dihkan, M.: Determination of geometric deformations in image registration using geometric and radiometric measurements. Sci. Res. Essays 5(3), 260–274 (2010)
Goshtasby, A.: Registration of images with geometric distortions. IEEE Trans. Geosci. Remote Sensing 26, 60–64 (1998)
Fitzpatrick, J.M., Hill, L.G., Maurer, R.: Medical image processing and analysis. Med. Imaging 2, 449–506 (2004)
Svedlow, M., Gillem, C.D., Anuta, P.E.: Experimental examination of similarity measures and preprocessing methods used for image registration. Mach. Process. Remotely Sensed Data 4, 9–17 (1976)
Pluim, W., Maintz, A., Viergever, A.: Mutual information-based registration of medical images: a survey. IEEE Trans. Med. Imaging 22(8), 986–1004 (2003)
Muratore, D.M., Russ, J., Dawant, B., Galloway, R.L.: Three-dimensional image registration of phantom vertebrae for image-guided surgery: a preliminary study. Comput. Aided Surg 7, 342–352 (2002)
Audette, M.A., Ferrie, F., Peters, T.: An algorithmic overview of surface registration techniques for medical imaging. Med. Image Anal 4(3), 201–217 (2000)
Santamaria, J., Cordon, O., Damas, S., Marti, R., Palma, J.: GRASP and path relinking hybridizations for the point matching-based image registration problem. J. Heuristics 18, 169–192 (2012)
Bholsithi, W., Sinthanayothin, C., Chintakanon, K., Komolpis, R., Tharanon, W.: Comparison between 3D and 2D cephalometric analyses. In: Proceedings of 4th Kuala Lumpur International Conference on Biomedical Engineering, BIOMED 2008, pp. 540–543. Kuala Lumpur, Malaysia (2008)
McIntyre, G.T., Mossey, P.A.: Size and shape measurement in contemporary cephalometrics. Eur. J. Orthod. 25, 231–242 (2003)
Goshtasby, A.: Registration of image with geometric distortion. IEEE Trans. Geosci. Remote Sens. 26(1), 60–64 (1988)
Bookstein, F.L.: Principal warps: thin-plate splines and the decomposition of deformations. IEEE Trans. Pattern Anal. Mach. Intell. 11(6), 567–585 (1989)
Mitra, J., Oliver, A., Marti, R., Llado, X., Vilanova, J., Meriaudeau, F.: A thin-plate spline based multimodal prostate registration with optimal correspondences. In: Proceedings of International Conference on Digital Image Computing, Techniques and Applications, DICTA 2010, pp. 330–380. Sydney, Australia (2010)
Xiao, K., Ho, S.H., Hassanien, A.E.: Brain magnetic resonance image lateral ventricles deformation analysis and tumor prediction. Malays. J. Comput. Sci. 20(2), 483–489 (2007)
Viola, P., William, M.: Alignment by maximization of mutual information. Int. J. Comput. Vision 24(2), 137–154 (1997)
Meyer, R., Jennifer, L., Boklye, K., Bland, H., Zasadny, R., Kison, V., Koral, K., Frey, A., Wahl, L.: Demonstration of accuracy and clinical versatility of mutual information for automatic multimodality image fusion using affine and thin-plate spline warped geometric deformations. Med. Image Anal. 1(3), 195–206 (1997)
Josien, P.W., Pluim, J.B., Antoine, M., Viergever, M.A.: Mutual information matching and interpolation artefacts. SPIE Med. Imag.: Image Processing 3661, 1–10 (1999)
Wirth, M., Narhan, J., Gray, D.: Nonrigid mammogram registration using mutual information. SPIE Med. Imag: Image Process. 4684, 562–573 (2002)
Kennedy, J. Eberhart, R.: Particle swarm optimization. In: Proceedings of the IEEE International Conference on Neural Network, IEEE Service Center Piscataway NJ, pp. 1942–1948. Perth, Australia (1995)
Shi, Y.: Particle swarm optimization. Proc. IEEE Int. Conf. Neural Netw. Soc. 4(13), 1942–1948 (2004)
Zhan, Z., Zhang, J., Yun, L., Shi, Y.: Orthogonal learning particle swarm optimization. IEEE Trans. Evol. Comput. 15(6), 832–847 (2011)
Shi, Y., Eberhart, R.: A modified particle swarm optimizer. In: Proceedings of IEEE World Congress on Computational Intelligence, pp. 69–73 (1998)
Ngan, D., Kharbanda, O., Geenty, J.: Comparison of radiation levels from computed tomography and conventional dental radiographs. Aust. Orthod. 19, 67–75 (2003)
Shankarapillai, R., Nair, M.: CAT imaging in periodontics and implant dentistry. Int. J. Dental Clinics 1, 8–12 (2009)
Banik, Sh, Rangayyan, R., Boag, G.: Landmarking and Segmentation of 3D CT images. Synth. Lect. Biomed. Eng. 4(1), 1–170 (2009)
Bholsithi, W., Sinthanayothin, C., Chintakanon, K., Komolpis, R., Tharanon, W.: Comparison between 3D and 2D cephalometric analyses. In: Proceedings of 4th Kuala Lumpur International Conference on Biomedical Engineering, BIOMED 2008, pp. 540–543. Kuala Lumpur, Malaysia (2008)
Innes, A., Ciesielski, V., Mamutil, J., John, S.: Finding templates for cephalometric landmark detection using pulse coupled neural networks and genetic programming. In: Proceedings of International Conference on Imaging Science, Systems and Technology, CISST03, vol 2, pp. 511–517. Las Vegas, Nevada, USA (2003)
Nassef, T., Solouma, N., Alkhodary, M., Marei, M., Kadah, Y.: Extraction of human mandible bones from multi-slice computed tomographic data. In: Proceedings of Conference on Biomedical Engineering (MECBME), pp. 260–263. 1st Middle East, Sharjah, United Arab Emirates (UAE) (2011)
Nassef, T., Solouma, N., Fliefel, R., Marei, M., Kadah, Y.: Computer assisted determination of mandibular cystic lesionvolume from computed tomographic data. In: Proceedings of Conference on Biomedical Engineering (MECBME), pp. 92–95. 1st Middle East, Sharjah, United Arab Emirates (UAE) (2011)
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Ahmed, S.A. (2016). Dental Image Registration Using Particle Swarm Optimized for Thin Plate Splines from Semi-automatic Correspondences. In: Hassanien, AE., Grosan, C., Fahmy Tolba, M. (eds) Applications of Intelligent Optimization in Biology and Medicine. Intelligent Systems Reference Library, vol 96. Springer, Cham. https://doi.org/10.1007/978-3-319-21212-8_4
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