Machine learning and coresets for automated real-time video segmentation of laparoscopic and robot-assisted surgery

Proceedings - IEEE International Conference on Robotics and Automation

Volumn , Issue , 2017, Pages 754-759

  Volkov, Mikhail ^a   Hashimoto, Daniel A ^b   Rosman, Guy ^a   Meireles, Ozanan R ^b   Rus, Daniela ^a  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b MASSACHUSETTS GENERAL HOSPITAL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATION; EDUCATION; IMAGE SEGMENTATION; LAPAROSCOPY; LEARNING SYSTEMS; ROBOTICS; ROBOTS; SURGERY; SURGICAL EQUIPMENT; VIDEO STREAMING;

COMPUTATIONAL RESOURCES; IMPROVE PERFORMANCE; LARGE AMOUNTS OF DATA; OPERATING ROOM ENVIRONMENT; REAL-TIME VIDEO SEGMENTATION; ROBOT-ASSISTED SURGERY; VARIABLE ENVIRONMENT; VIDEO SEGMENTATION;

ROBOTIC SURGERY;

EID: 85027994751     PISSN: 10504729     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICRA.2017.7989093     Document Type: Conference Paper

References (32)

1. M. Allan, P.-L. Chang, S. Ourselin, D. J. Hawkes, A. Sridhar, J. Kelly, and D. Stoyanov. Image based surgical instrument pose estimation with multi-class labelling and optical flow. In International Conference on Medical Image Computing and Computer-Assisted Intervention, pages 331-338. Springer, 2015.
2. T. Blum, H. Feußner, and N. Navab. Modeling and segmentation of surgical workflow from laparoscopic video. In International Conference on Medical Image Computing and Computer-Assisted Intervention, pages 400-407. Springer, 2010.
3. E. M. Bonrath, N. J. Dedy, L. E. Gordon, and T. P. Grantcharov. Comprehensive surgical coaching enhances surgical skill in the operating room: a randomized controlled trial. Annals of surgery, 262(2):205-212, 2015.
4. L. Bouarfa, P. Jonker, and J. Dankelman. Surgical context discovery by monitoring low-level activities in the or. In MICCAI workshop on modeling and monitoring of computer assisted interventions (M2CAI). London, UK, 2009.
5. L. Bouarfa, P. P. Jonker, and J. Dankelman. Discovery of high-level tasks in the operating room. Journal of biomedical informatics, 44(3):455-462, 2011.
6. D. Bouget, R. Benenson, M. Omran, L. Riffaud, B. Schiele, and P. Jannin. Detecting surgical tools by modelling local appearance and global shape. IEEE transactions on medical imaging, 34(12):2603-2617, 2015.
7. A. F. Costa, G. Humpire-Mamani, and A. J. M. Traina. An efficient algorithm for fractal analysis of textures. In Graphics, Patterns and Images (SIBGRAPI), 2012 25th SIBGRAPI Conference on, pages 39-46. IEEE, 2012.
8. O. Dergachyova, D. Bouget, A. Huaulme, X. Morandi, and P. Jannin. Automatic data-driven real-time segmentation and recognition of surgical workflow. International journal of computer assisted radiology and surgery, pages 1-9, 2016.
9. B. L. Ecker, R. Maduka, A. Ramdon, D. T. Dempsey, K. R. Dumon, and N. N. Williams. Resident education in robotic-assisted vertical sleeve gastrectomy: outcomes and cost-analysis of 411 consecutive cases. Surgery for Obesity and Related Diseases, 2015.
10. K. Kahol, N. C. Krishnan, V. N. Balasubramanian, S. Panchanathan, M. Smith, and J. Ferrara. Measuring movement expertise in surgical tasks. In Proceedings of the 14th ACM international conference on Multimedia, pages 719-722. ACM, 2006.
11. U. Kannan, B. L. Ecker, R. Choudhury, D. T. Dempsey, N. N. Williams, and K. R. Dumon. Laparoscopic hand-assisted versus robotic-assisted laparoscopic sleeve gastrectomy: experience of 103 consecutive cases. Surgery for Obesity and Related Diseases, 2015.
12. M. Kranzfelder, A. Schneider, A. Fiolka, E. Schwan, S. Gillen, D. Wilhelm, R. Schirren, S. Reiser, B. Jensen, and H. Feussner. Real-time instrument detection in minimally invasive surgery using radiofrequency identification technology. journal of surgical research, 185(2):704-710, 2013.
13. F. Lalys, L. Riffaud, D. Bouget, and P. Jannin. A framework for the recognition of high-level surgical tasks from video images for cataract surgeries. IEEE Transactions on Biomedical Engineering, 59(4):966-976, 2012.
14. F. Lalys, L. Riffaud, X. Morandi, and P. Jannin. Automatic phases recognition in pituitary surgeries by microscope images classification. In International Conference on Information Processing in Computer-Assisted Interventions, pages 34-44. Springer, 2010.
15. F. Lalys, L. Riffaud, X. Morandi, and P. Jannin. Surgical phases detection from microscope videos by combining SVM and HMM. In Medical Computer Vision. Recognition Techniques and Applications in Medical Imaging, pages 54-62. Springer, 2010.
16. B. P. Lo, A. Darzi, and G.-Z. Yang. Episode classification for the analysis of tissue/instrument interaction with multiple visual cues. In MICCAI, pages 230-237. Springer, 2003.
17. G. Marangoni, G. Morris-Stiff, S. Deshmukh, A. Hakeem, and A. M. Smith. A modern approach to teaching pancreatic surgery. Journal of gastrointestinal surgery, 16(8):1597-1604, 2012.
18. N. Mehta, R. Haluck, M. Frecker, and A. Snyder. Sequence and task analysis of instrument use in common laparoscopic procedures. Surgical Endoscopy And Other Interventional Techniques, 16(2):280-285, 2002.
19. T. Neumuth and C. Meißner. Online recognition of surgical instruments by information fusion. International journal of computer assisted radiology and surgery, 7(2):297-304, 2012.
20. N. Padoy, T. Blum, S.-A. Ahmadi, H. Feussner, M.-O. Berger, and N. Navab. Statistical modeling and recognition of surgical workflow. Medical image analysis, 16(3):632-641, 2012.
21. N. Padoy, T. Blum, I. Essa, H. Feussner, M.-O. Berger, and N. Navab. A boosted segmentation method for surgical workflow analysis. In International Conference on Medical Image Computing and Computer-Assisted Intervention, pages 102-109. Springer, 2007.
22. N. Padoy, T. Blum, H. Feussner, M.-O. Berger, and N. Navab. On-line recognition of surgical activity for monitoring in the operating room. In AAAI, pages 1718-1724, 2008.
23. A. Reiter, P. K. Allen, and T. Zhao. Feature classification for tracking articulated surgical tools. In International Conference on Medical Image Computing and Computer-Assisted Intervention, pages 592-600. Springer, 2012.
24. N. Rieke, D. J. Tan, M. Alsheakhali, F. Tombari, C. A. di San Filippo, V. Belagiannis, A. Eslami, and N. Navab. Surgical tool tracking and pose estimation in retinal microsurgery. In International Conference on Medical Image Computing and Computer-Assisted Intervention, pages 266-273. Springer, 2015.
25. J. Rosen, M. Solazzo, B. Hannaford, and M. Sinanan. Task decomposition of laparoscopic surgery for objective evaluation of surgical residents' learning curve using hidden markov model. Computer Aided Surgery, 7(1):49-61, 2002.
26. G. Rosman, M. Volkov, D. Feldman, J. W. Fisher III, and D. Rus. Coresets for k-segmentation of streaming data. In NIPS, pages 559-567. Curran Associates, Inc., 2014.
27. P. Singh, R. Aggarwal, M. Tahir, P. H. Pucher, and A. Darzi. A randomized controlled study to evaluate the role of video-based coaching in training laparoscopic skills. Annals of surgery, 261(5):862-869, 2015.
28. S. Speidel, J. Benzko, S. Krappe, G. Sudra, P. Azad, B. P. Müller-Stich, C. Gutt, and R. Dillmann. Automatic classification of minimally invasive instruments based on endoscopic image sequences. In SPIE Medical Imaging, pages 72610A-72610A. International Society for Optics and Photonics, 2009.
29. R. Stauder, A. Okur, L. Peter, A. Schneider, M. Kranzfelder, H. Feussner, and N. Navab. Random forests for phase detection in surgical workflow analysis. In International Conference on Information Processing in Computer-Assisted Interventions, pages 148-157. Springer, 2014.
30. R. Sznitman, C. Becker, and P. Fua. Fast part-based classification for instrument detection in minimally invasive surgery. In International Conference on Medical Image Computing and Computer-Assisted Intervention, pages 692-699. Springer, 2014.
31. M. Volkov, G. Rosman, D. Feldman, J. W. Fisher III, and D. Rus. Coresets for visual summarization with applications to loop closure. In ICRA, Seattle, Washington, USA, May 2015. IEEE.
32. E. Wild, D. Teber, D. Schmid, T. Simpfendorfer, M. Müller, A.-C. Baranski, H. Kenngott, K. Kopka, and L. Maier-Hein. Robust augmented reality guidance with fluorescent markers in laparoscopic surgery. International journal of computer assisted radiology and surgery, pages 1-9, 2016.