Abstract
This paper presents a new method to reconstruct the beating heart surface based on the non-rigid structure from motion technique using preprocessed endoscopic images. First the images captured at the same phase within each heart cycle are automatically extracted from the original image sequence to reduce the dimension of the deformation subspace. Then the remaining residual non-rigid motion is restricted to lie within a low-dimensional subspace and a probabilistic model is used to recover the 3D structure and camera motion simultaneously. Outliers are removed iteratively based on the reprojection error. Missing data are also recovered with an Expectation Maximization algorithm. As a result the camera can move around the operation scene to build a 3D surface with a wide field-of-view for intra-operative procedures. The method has been evaluated with synthetic data, heart phantom data, and in vivo data from a da Vinci surgical system.
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Devernay, F., Mourgues, F., Coste-Maniere, E.: Towards Endoscopic Augmented Reality for Robotically Assisted Minimally Invasive Cardiac Surgery. In: Proc. International Workshop on Medical Imaging and Augmented Reality, pp. 16–20 (2001)
Lau, W.W., Ramey, N.A., Corso, J.J., Thakor, N.V., Hager, G.D.: Stereo-Based Endoscopic Tracking of Cardiac Surface Deformation. In: Barillot, C., Haynor, D.R., Hellier, P. (eds.) MICCAI 2004. LNCS, vol. 3217, pp. 494–501. Springer, Heidelberg (2004)
Bader, T., Wiedemann, A., Roberts, K., Hanebeck, U.D.: Model-Based Motion Estimation of Elastic Surfaces for Minimally Invasive Cardiac Surgery. In: Proc. ICRA, pp. 2261–2266 (2007)
Mountney, P., Stoyanov, D., Davison, A.J., Yang, G.-Z.: Simultaneous Stereoscope Localization and Soft-Tissue Mapping for Minimal Invasive Surgery. In: Larsen, R., Nielsen, M., Sporring, J. (eds.) MICCAI 2006. LNCS, vol. 4190, pp. 347–354. Springer, Heidelberg (2006)
Hu, M., Penney, G.P., Edwards, P., Figl, M., Hawkes, D.J.: 3D Reconstruction of Internal Organ Surfaces for Minimal Invasive Surgery. In: Ayache, N., Ourselin, S., Maeder, A. (eds.) MICCAI 2007, Part I. LNCS, vol. 4791, pp. 68–77. Springer, Heidelberg (2007)
Hu, M., Penney, G.P., Rueckert, D., Edwards, P., Figl, M., Pratt, P., Hawkes, D.J.: A Novel Algorithm for Heart Motion Analysis Based on Geometric Constraints. In: Metaxas, D., Axel, L., Fichtinger, G., Székely, G. (eds.) MICCAI 2008, Part I. LNCS, vol. 5241, pp. 720–728. Springer, Heidelberg (2008)
Zhang, Z.: A Flexible New Technique for Camera Calibration. IEEE Trans. PAMI 22(11), 1330–1334 (2000)
Torresani, L., Hertzmann, A., Bregler, C.: Learning Non-Rigid 3D Shape from 2D Motion. In: Proc. NIPS, pp. 1555–1562 (2004)
Torresani, L., Hertzmann, A., Bregler, C.: Nonrigid Structure-from-Motion: Estimating Shape and Motion with Hierarchical Priors. IEEE Trans. PAMI 30(5), 878–892 (2008)
Tomasi, C., Kanade, T.: Shape and Motion from Image Streams under Orthography: a Factorization Method. Int. J. Computer Vision 9(2), 137–154 (1992)
Bregler, C., Hertzmann, A., Biermann, H.: Recovering Non-Rigid 3D Shape from Image Streams. In: Proc. CVPR, pp. 690–696 (2000)
Fischler, M.A., Bolles, R.C.: Random sample consensus: a paradigm for model fitting with applications to image analysis. Comm. ACM 24, 381–385 (1981)
Lucas, B., Kanade, T.: An Iterative Image Registration Technique with an Application to Stereo Vision. In: Proc. IJCAI, pp. 674–679 (1981)
Image registration toolkit, http://www.doc.ic.ac.uk/~dr/software/
Besl, P., McKay, N.: A Method for Registration of 3-D Shapes. IEEE Trans. PAMI 14(2), 239–256 (1992)
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Hu, M. et al. (2009). Non-rigid Reconstruction of the Beating Heart Surface for Minimally Invasive Cardiac Surgery. In: Yang, GZ., Hawkes, D., Rueckert, D., Noble, A., Taylor, C. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009. MICCAI 2009. Lecture Notes in Computer Science, vol 5761. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04268-3_5
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