No data available.
Please log in to see this content.
You have no subscription access to this content.
No metrics data to plot.
The attempt to load metrics for this article has failed.
The attempt to plot a graph for these metrics has failed.
Dense GPU-enhanced surface reconstruction from stereo endoscopic images for intraoperative registration
1. R. Maciunas, “Computer-assisted neurosurgery,” Clin. Neurosurg. 53, 267 (2006).
2. A. Malti, A. Bartoli, and T. Collins, “Template-based conformal shape-from-motion from registered laparoscopic images,” Proceedings of Medical Image Understanding and Analysis Conference (IEEE Computer Society, Washington, DC, 2011).
3. S. Lee, M. Lerotic, V. Vitiello, S. Giannarou, K. Kwok, M. Visentini-Scarzanella, and G. Yang, “From medical images to minimally invasive intervention: Computer assistance for robotic surgery,” Comput. Med. Imaging Graph. 34(1), 33–45 (2010).
4. P. Sánchez-González, A. Cano, I. Oropesa, F. Sánchez-Margallo, F. Del Pozo, P. Lamata, and E. Gómez, “Laparoscopic video analysis for training and image-guided surgery,” Minimally Invasive Ther. Allied Technol. 20(6), 311–320 (2011).
5. P. Mountney and G. Yang, “Motion compensated slam for image guided surgery,” Proceedings of MICCAI (MICCAI Society, Minnesota, 2010), Vol. 6362, pp. 496–504.
6. J. Ackerman, K. Keller, and H. Fuchs, “Surface reconstruction of abdominal organs using laparoscopic structured light for augmented reality,” Proc. SPIE Med. Imaging 4661, 39–46 (2002).
7. N. Clancy, D. Stoyanov, G. Yang, and D. Elson, “An endoscopic structured lighting probe using spectral encoding,” Proc. SPIE Med. Imaging 8090, 809002 (2011).
8. J. Penne, K. Höller, M. Stürmer, T. Schrauder, A. Schneider, R. Engelbrecht, H. Feußner, B. Schmauss, and J. Hornegger, “Time-of-flight 3-d endoscopy,” Proceedings of MICCAI (MICCAI Society, Minnesota, 2009), Vol. 5761, pp. 467–474.
10. C. Wu, Y. Sun, and C. Chang, “Three-dimensional modeling from endoscopic video using geometric constraints via feature positioning,” IEEE Trans. Biomed. Eng. 54(7), 1199–1211 (2007).
11. M. Hu, G. Penney, M. Figl, P. Edwards, F. Bello, R. Casula, D. Rueckert, and D. Hawkes, “Reconstruction of a 3D surface from video that is robust to missing data and outliers: Application to minimally invasive surgery using stereo and mono endoscopes,” Med. Image Anal. 15 (2011).
12. P. Mountney and G. Yang, “Soft tissue tracking for minimally invasive surgery: Learning local deformation online,” Proceedings of MICCAI (MICCAI Society, Minnesota, 2008), Vol. 5242, pp. 364–372.
13. D. Stoyanov, M. Scarzanella, P. Pratt, and G. Yang, “Real-time stereo reconstruction in robotically assisted minimally invasive surgery,” Proceedings of MICCAI (MICCAI Society, Beijing, China, 2010), Vol. 6361, pp. 275–282.
14. C. Chen, D. Sargent, C. Tsai, Y. Wang, and D. Koppel, “Stabilizing stereo correspondence computation using delaunay triangulation and planar homography,” LECT NOTES COMPUT SC 5358/2008, 836–845 (2008).
16. W. Lau, N. Ramey, J. Corso, N. Thakor, and G. Hager, “Stereo-based endoscopic tracking of cardiac surface deformation,” Proceedings of MICCAI (MICCAI Society, Minnesota, 2004), Vol. 3217, pp. 494–501.
17. F. Devernay, F. Mourgues, and E. Coste-Maniere, “Towards endoscopic augmented reality for robotically assisted minimally invasive cardiac surgery,” Proceedings of Medical Imaging and Augmented Reality (MIAR) (The University of Tokio, Japan, 2001), pp. 16–20.
18. D. Stoyanov, A. Darzi, and G. Yang, “A practical approach towards accurate dense 3d depth recovery for robotic laparoscopic surgery,” Comput. Aided Surg. 4, 199–208 (2005).
19. B. Vagvolgyi, L. Su, R. Taylor, and G. Hager, “Video to CT registration for image overlay on solid organs,” Proceedings of Augmented Reality in Medical Imaging and Augmented Reality in Computer-Aided Surgery (AMIARCS) (Imperial College, London, UK, 2008), pp. 78–86.
20. S. Röhl, S. Bodenstedt, S. Suwelack, H. Kenngott, B. Müller-Stich, R. Dillmann, and S. Speidel, “Real-time surface reconstruction from stereo endoscopic images for intraoperative registration,” Proc. SPIE Med. Imaging 7964, 796414 (2011).
21. S. Röhl, S. Speidel, D. Gonzalez-Aguirre, S. Suwelack, H. Kenngott, T. Asfour, B. Müller-Stich, and R. Dillmann, “From stereo image sequences to smooth and robust surface models using temporal information and bilateral postprocessing,” IEEE International conference on Robotics and Biomimetics (ROBIO) (IEEE Computer Society, Washington, DC, 2011).
23. C. Chou, Y. Chuo, Y. Hung, and W. Wang, “A fast forward projection using multithreads for multirays on GPUs in medical image reconstruction,” Med. Phys. 38, 4052 (2011).
24. H. Hofmann, B. Keck, C. Rohkohl, and J. Hornegger, “Comparing performance of many-core CPUs and GPUs for static and motion compensated reconstruction of c-arm CT data,” Med. Phys. 38, 468 (2011).
25. L. Persoon, M. Podesta, W. van Elmpt, S. Nijsten, and F. Verhaegen, “A fast three-dimensional gamma evaluation using a GPU utilizing texture memory for on-the-fly interpolations,” Med. Phys. 38, 4032 (2011).
27. J. Wu, M. Kim, J. Peters, H. Chung, and S. Samant, “Evaluation of similarity measures for use in the intensity-based rigid 2D-3D registration for patient positioning in radiotherapy,” Med. Phys. 36, 5391 (2009).
28. J. Spoerk, H. Bergmann, F. Wanschitz, S. Dong, and W. Birkfellner, “Fast drr splat rendering using common consumer graphics hardware,” Med. Phys. 34, 4302 (2007).
29. P. Azad, T. Gockel, and R. Dillmann, Computer Vision: Principles and Practice (Elektor-Verlag, Aachen, Germany, 2007).
31. N. Atzpadin, P. Kauff, and O. Schreer, “Stereo analysis by hybrid recursive matching for real-time immersive video conferencing,” IEEE Transactions on Circuits and Systems for Video Technology (IEEE Computer Society, Washington, DC, 2004) Vol. 14.
32. S. Paris, P. Kornprobst, J. Tumblin, and F. Durand, “A gentle introduction to bilateral filtering and its applications,” ACM SIGGRAPH 2007 courses (Association for Computing Machinery, Inc., New York City, 2007), p. 1.
35. N. Mitra, N. Gelfand, H. Pottmann, and L. Guibas, “Registration of point cloud data from a geometric optimization perspective,” Proceedings of Eurographics/ACM SIGGRAPH Symposium on Geometry Processing (43 Association for Computing Machinery, Inc., New York City, USA 2004), pp. 22–31.
39. S. Bodenstedt, S. Röhl, S. Suwelack, D. Katic, H. Kenngott, B. Müller-Stich, R. Dillmann, and S. Speidel, “A flexible framework for multiple sensor integration in to a context-aware cas-system,” Computer Assisted Radiology and Surgery (CARS) (CARS Society, Kuessaberg, Germany, 2011).
40. P. Pratt, D. Stoyanov, M. Visentini-Scarzanella, and G. Yang, “Dynamic guidance for robotic surgery using image-constrained biomechanical models,” Proceedings of MICCAI (MICCAI Society, Minnesota, 2010), Vol. 6361, 77–85.
42. Q. Yang, L. Wang, and N. Ahuja, “A constant-space belief propagation algorithm for stereo matching,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (IEEE Computer Society, Washington, DC, 2010), 1458–1465.
43. G. Bradski and A. Kaehler, Learning OpenCV: Computer vision with the OpenCV library (O’Reilly Media, Sebastopol, 2008).
44. W. Press et al., Numerical Recipes (Cambridge University Press, Cambridge, UK, 2007), Vol. 3.
Article metrics loading...
Full text loading...
Most read this month