Toward long-term and accurate Augmented-Reality display for minimally-invasive surgery

Proceedings - IEEE International Conference on Robotics and Automation

Volumn , Issue , 2013, Pages 5384-5389

  Puerto Souza, Gustavo A ^a   Mariottini, Gian Luca ^a  

^a The University of Texas at Arlington   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

FEATURE MATCHING; ILLUMINATION CHANGES; INTRA-OPERATIVE; LEAST-SQUARES APPROACH; MINIMALLY INVASIVE SURGERY; MONOCULAR VIDEO; SURGICAL DISPLAY; VISUAL AWARENESS;

SURGERY;

ROBOTICS;

EID: 84887291336     PISSN: 10504729     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICRA.2013.6631349     Document Type: Conference Paper

References (22)

1. L.M.Su, B.P.Vagvolgyi, R.Agarwal, C.E.Reiley, R.H.Taylor, and G.D.Hager.Augmented reality during robot-assisted laparoscopic partial nephrectomy: Toward real-time 3d-ct to stereoscopic video registration.Urology, 73(4):896-900, 2009.
2. D.Cohen, E.Mayer, D.Chen, A.Anstee, J.Vale, G.Z.Yang, A.Darzi, and P.Edwards.Augmented reality image guidance in minimally invasive prostatectomy.Prostate Cancer Imaging.Computer-Aided Diagnosis, Prognosis, and Intervention, pages 101-110, 2010.
3. B.Vagvolgyi, Li-Ming Su, R.Taylor, and G.D.Hager.Video to ct registration for image overlay on solid organs.In 4th Workshop on Augmented Environments for Medical Imaging and Computer-Aided Surgery, 2008.
4. T.Simpfendorfer, M.Baumhauer, M.Muller, C.N.Gutt, H.P.Meinzer, J.J.Rassweiler, S.Guven, and D.Teber.Augmented reality visualization during laparoscopic radical prostatectomy.Journal of endourology, 25(12):1841-1845, 2011.
5. E.Higgins William, P.Helferty James, Lu Kongkuo, A.Merritt Scott, Rai Lav, and Yu Kun-Chang.3d ct-video fusion for imageguided bronchoscopy. Computerized Medical Imaging and Graphics, 32(3):159-173, 2008.
6. R.Richa, A.P.L Bo, and P.Poignet.Towards robust 3d visual tracking for motion compensation in beating heart surgery.Medical Image Analysis, 2010.
7. D.Stoyanov, G.Mylonas, F.Deligianni, A.Darzi, and G.-Z.Yang.Soft-tissue motion tracking and structure estimation for robotic assisted mis procedures.Medical Image Computing and Computer-Assisted Intervention-MICCAI 2005, pages 139-146, 2005.
8. P.Mountney and G.Z.Yang.Motion compensated slam for image guided surgery.Medical Image Computing and Computer-Assisted Intervention, pages 496-504, 2010.
9. S.Giannarou, M.Visentini-Scarzanella, and G.Yang.Probabilistic tracking of affine-invariant anisotropic regions.IEEE T.PAMI, 2012.
10. M.Yip, D.Lowe, S.Salcudean, R.Rohling, and C.Nguan.Real-time methods for long-term tissue feature tracking in endoscopic scenes.Information Processing in Computer-Assisted Interventions, pages 33-43, 2012.
11. G.A.Puerto-Souza and G.L.Mariottini.Hierarchical multi-affine (HMA) algorithm for fast and accurate feature matching in minimallyinvasive surgical images.In 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (accepted), 2012.
12. D.G.Lowe.Distinctive image features from scale-invariant keypoints.Int.J.Comp.Vis., 60(2):91-110, 2004.
13. M.Cho, J.Lee, and K.M.Lee.Feature correspondence and deformable object matching via agglomerative correspondence clustering.In Proc.9th Int.Conf.Comp.Vis., pages 1280-1287, 2009.
14. G.A.Puerto-Souza, M.Adibi, J.A.Cadeddu, and G.L.Mariottini.Adaptive multi-affine (ama) feature-matching algorithm and its application to minimally-invasive surgery images.In 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 2371-2376, sept.2011.
15. R.Szeliski.Computer vision: algorithms and applications.Springer-Verlag New York Inc, 2010.
16. K.Mikolajczyk and C.Schmid.A performance evaluation of local descriptors.IEEE Trans.Pattern Anal., 60:1615-1630, 2005.
17. P.Mountney, B.Lo, S.Thiemjarus, D.Stoyanov, and G.-Z.Yang.A probabilistic framework for tracking deformable soft tissue in minimally invasive surgery.Medical Image Computing and Computer-Assisted Intervention, pages 34-41, 2007.
18. A.Del Bimbo, F.Franco, and F.Pernici.Local shape estimation from a single keypoint.In Proc.Comp.Vis.Patt.Rec.Workshops, pages 23-28, 2010.
19. J.Hailin, P.Favaro, and S.Soatto.Real-time feature tracking and outlier rejection with changes in illumination.In Proc.IEEE Intern.Conf.on Computer Vision, volume 1, pages 684-689, 2001.
20. J.Shi and C.Tomasi.Good features to track.In Proc.IEEE Int.Conf.Comp.Vis.Patt.Rec., pages 593-600, June 1994.
21. R.Hartley and A.Zisserman.Multiple view geometry in computer vision.Cambridge Univ Press, 2000.
22. C.Nadeau and A.Krupa.Improving ultrasound intensity-based visual servoing: tracking and positioning tasks with 2d and bi-plane probes.In 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 2837-2842.IEEE, 2011.