Abstract
This paper introduces a fast non-rigid registration method for aligning pre-operative 1.5 T MR images to intra-operative 0.5 T MR images for guidance in prostate biopsy.
After the acquisition of both pre-operative 1.5 T and intra-operative 0.5 T, an intensity correction method is applied to the pre-operative images to reduce the significant artifacts in the signal intensities due to the presence of an endo-rectal coil. A fast manual segmentation of prostate in both modalities is carried out to enable conformal map** of the surface of the pre-operative data to the intra-operative data. A displacement field is estimated with a linear elastic inhomogeneous material model using the surface displacements established by the conformal map**. We then use this as an initialization for a mutual information based non-rigid registration algorithm to match the internal structures of the prostate. This non-rigid registration is based on a finite element method discretization using the mutual information metric with a linear elastic regularization constraint. The registration is accelerated while preserving accuracy by using an adaptive mesh based on the body-centered cubic lattice and a significantly improved registration is achieved.
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Angenent, S., Haker, S., Tannenbaum, A., Kikinis, R.: On the laplace-beltrami operator and brain surface flattening. IEEE Trans. Med. Imaging 18, 700–711 (1999)
Bansal, R., Staib, L., Chen, Z., Rangarajan, A., Knisely, J., Nath, R., Duncan, J.S.: Entropy-based, multiple-portal-to-3dct registration for prostate radiotherapy using iteratively estimate segmentation. In: Taylor, C., Colchester, A. (eds.) MICCAI 1999. LNCS, vol. 1679, pp. 567–578. Springer, Heidelberg (September 1999)
Bharatha, M., Hirose, N., Hata, S., Warfield, M., Ferrant, K., Zou, E., Suarez- Santana, J., Ruiz-Azola, A., D’Amico, R., Cormack, F., Jolesz, F., Tempany, C.: Evaluation of three-dimensional finite element-based deformable registration of pre- and intra-operative prostate imaging. Med. Phys. (2001)
Cabello, J., Lohner, R., Jacquote, O.P.: A variational method for the optimization of two and three-dimensional unstructured meshes. Technical report, Technical Report AIAA-92-0450 (1992)
Court, L., Dong, L.: Automatic registration of the prostate for computedtomography-guided radiotherapy. Med. Phys. (2003)
De Craene, M., du Bois d Aische, A., Talos, I., Ferrant, M., Black, P., Jolesz, F., Kikinis, R., Macq, B., Warfield, S.: Dense deformation field estimation for brain intra-operative images registration. In: SPIE Medical imaging (2004)
De Craene, M., du Bois d’Aische, A., Weisenfeld, N., Haker, S., Macq, B., Warfield, S.: Multi-modal non-rigid registration using a stochastic gradient approximation. In: ISBI (2004)
Ferrant, M., Nabavi, A., Macq, B., Black, P.M., Jolesz, F.A., Kikinis, R., Warfield, S.K.: Serial Registration of Intraoperative MR Images of the Brain. Med. Image Anal. 6(4), 337–359 (2002)
Freitag, L., Leurent, T., Knupp, P., Melander, D.: Mesquite design: Issues in the development of a mesh quality improvement toolki. In: Proceedings of the 8th Intl. Conference on Numerical Grid Generation in Computational Field Simulation, pp. 159–168 (2002)
Gering, D., Nabavi, A., Kikinis, R., Grimson, W.E.L., Hata, N., Everett, P., Jolesz, F., Wells, W.: An integrated visualization system for surgical planning and guidance using image fusion and interventional imaging. In: Taylor, C., Colchester, A. (eds.) MICCAI 1999. LNCS, vol. 1679, pp. 809–819. Springer, Heidelberg (1999)
Ibanez, L., Schroeder, W., Ng, L., Cates .: The ITK Software Guide. The Insight Consortium, http://www.itk.org
Mangin, J.-F.: Entropy minimization for automatic correction of intensity nonuniformity. In: Mathematical Methods in Biomedical Image Analysis, California, pp. 162–169. IEEE Computer Society, Los Alamitos (2000)
Mattes, D., Haynor, D.R., Vesselle, H., Lewellen, T.K., Eubank, W.: Pet-ct image registration in the chest using free-form deformations. IEEE Transaction on Medical Imaging 22(1), 120–128 (2003)
Molino, N., Bridson, R., Teran, J., Fedkiw, R.: A crystalline, red green strategy for meshing highly deformable objects with tetrahedra. 12th International Meshing Roundtable,Sandia National Laboratories, 103–114 (September 2003)
Spall, J.C.: Overview of the simultaneous perturbation method for efficient optimization. Hopkins APL Technical Digest 19, 482–492 (1998), http://techdigest.jhuapl.edu/td/td1904/spall.pdf
Viola, P., Wells III., W.M.: Alignment by maximization of mutual information. In: Fifth Int. Conf. on Computer Vision, pp. 16–23 (1995)
Zienkiewicz, O.C., Taylor, R.L.: The Finite Element Method,4th edn. In: Basic Formulation and Linear Problems, vol. 1. McGraw-Hill, London (1989)
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du Bois d’Aische, A. et al. (2004). Improved Non-rigid Registration of Prostate MRI. In: Barillot, C., Haynor, D.R., Hellier, P. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2004. MICCAI 2004. Lecture Notes in Computer Science, vol 3216. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30135-6_103
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DOI: https://doi.org/10.1007/978-3-540-30135-6_103
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