Real-time dense stereo reconstruction using convex optimisation with a cost-volume for image-guided robotic surgery

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 8149 LNCS, Issue PART 1, 2013, Pages 42-49

  Chang, Ping Lin ^a   Stoyanov, Danail ^b   Davison, Andrew J ^a   Edwards, Philip ^a  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

^b UNIVERSITY COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURATE GUIDANCE; CONVEX OPTIMISATION; DEPTH DISCONTINUITIES; ENDOSCOPIC IMAGING; MINIMALLY INVASIVE SURGERY; QUANTITATIVE EVALUATION; STATE-OF-THE-ART METHODS; STEREO RECONSTRUCTION;

ALGORITHMS; ENDOSCOPY; OPTIMIZATION; ROBOTICS; SURGERY;

IMAGE RECONSTRUCTION;

ALGORITHM; ARTICLE; COMPUTER ASSISTED DIAGNOSIS; COMPUTER ASSISTED SURGERY; COMPUTER SYSTEM; ENDOSCOPY; EQUIPMENT; HUMAN; IMAGE ENHANCEMENT; IMAGE QUALITY; METHODOLOGY; REPRODUCIBILITY; ROBOTICS; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING;

ALGORITHMS; COMPUTER SYSTEMS; ENDOSCOPY; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; PHANTOMS, IMAGING; REPRODUCIBILITY OF RESULTS; ROBOTICS; SENSITIVITY AND SPECIFICITY; SURGERY, COMPUTER-ASSISTED;

EID: 84885816827     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-40811-3_6     Document Type: Conference Paper

References (16)

1. Chambolle, A., Pock, T.: A first-order primal-dual algorithm for convex problems with applications to imaging. Journal of Mathematical Imaging and Vision 40(1), 120-145 (2011) 45
2. Chang, P.-L., Chen, D., Cohen, D., Edwards, P.E.: 2D/3D registration of a preoperative model with endoscopic video using colour-consistency. In: Linte, C.A., Moore, J.T., Chen, E.C.S., Holmes III, D.R. (eds.) AE-CAI 2011. LNCS, vol. 7264, pp. 1-12. Springer, Heidelberg (2012) 42
3. Devernay, F., Mourgues, F., Coste-Maniere, E.: Towards endoscopic augmented reality for robotically assisted minimally invasive cardiac surgery. In: International Workshop on Medical Imaging and Augmented Reality, pp. 16-20 (2001) 42, 43
4. Handa, A., Newcombe, R.A., Angeli, A., Davison, A.J.: Applications of legendrefenchel transformation to computer vision problems. Tech. Rep. DTR11-7, Department of Computing at Imperial College London (2011) 45
5. 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) 43
6. Mirota, D.J., Ishii, M., Hager, G.D.: Vision-based navigation in image-guided interventions. Annual Review of Biomedical Engineering 13, 297-319 (2011) 42, 43
7. Mountney, P., Stoyanov, D., Yang, G.-Z.: Three-dimensional tissue deformation recovery and tracking. IEEE Signal Processsing Magazine 27(4), 14-24 (2010) 42, 43
8. Rhemann, C., Hosni, A., Bleyer, M., Rother, C., Gelautz, M.: Fast cost-volume filtering for visual correspondence and beyond. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3017-3024 (2011) 44, 47, 48
9. Richa, R., Bo, A.P.L., Poignet, P.: Towards robust 3D visual tracking for motion compensation in beating heart surgery. Medical Image Analysis 15(3), 302-315 (2011) 43
10. Rohl, S., Bodenstedt, S., Suwelack, S., Dillmann, R., Speidel, S., Kenngott, H., Muller-Stich, B.P.: Dense GPU-enhanced surface reconstruction from stereo endoscopic images for intraoperative registration. Medical Physics 39(3), 1632-1645 (2012) 43, 44, 47
11. Rudin, L., Osher, S., Fatemi, E.: Nonlinear total variation based noise removal algorithms. Physica D: Nonlinear Phenomena 60(1-4), 259-268 (1992) 45
12. Scharstein, D., Szeliski, R.: A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. International Journal of Computer Vision (1), 131-140 (2002) 43
13. Steinbrucker, F., Pock, T., Cremers, D.: Large displacement optical flow computation without warping. In: IEEE International Conference on Computer Vision (ICCV), pp. 1609-1614 (2009) 45
14. Stoyanov, D.: Stereoscopic scene flow for robotic assisted minimally invasive surgery. In: Ayache, N., Delingette, H., Golland, P., Mori, K. (eds.) MICCAI 2012, Part I. LNCS, vol. 7510, pp. 479-486. Springer, Heidelberg (2012) 47
15. Stoyanov, D., Scarzanella, M.V., Pratt, P., Yang, G.-Z.: Real-time stereo reconstruction in robotically assisted minimally invasive surgery. In: Jiang, T., Navab, N., Pluim, J.P.W., Viergever, M.A. (eds.) MICCAI 2010, Part I. LNCS, vol. 6361, pp. 275-282. Springer, Heidelberg (2010) 42, 43, 47, 48
16. Werlberger, M., Trobin, W., Pock, T., Wedel, A., Cremers, D., Bischof, H.: Anisotropic Huber-L1 Optical Flow. In: British Machine Vision Conference (BMVC), pp. 108.1-108.11 (2009) 45