research-article

A comparative study on 3-D stereo reconstruction from endoscopic images

Authors:

Mostafa Parchami,

Gian-Luca MariottiniAuthors Info & Claims

PETRA '14: Proceedings of the 7th International Conference on PErvasive Technologies Related to Assistive Environments

Article No.: 25, Pages 1 - 8

https://doi.org/10.1145/2674396.2674425

Published: 27 May 2014 Publication History

Abstract

Advances in robotic surgery and growing use of robots in minimal access surgery (MAS), has increased the need of adapting computer-vision algorithms for surgical-vision applications. While methods for 3-D reconstruction are extensively investigated on man-made environments, the surgical-vision lacks such studies on 3-D reconstruction methods and their pros and cons on endoscopic images. In this paper we extensively compared several dense stereo reconstruction methods on a mock-up model using videos acquired from the daVinci endoscope. Also, the advantages and disadvantages of each method for different stages of stereo reconstruction are mentioned and supported by exhaustive experiments on endoscopic images.

References

[1]

Gian-luca mariottini. http://egt.dii.unisi.it. Accessed: 2014-02-15.

[2]

Point cloud library. http://pointclouds.org. Accessed: 2014-02-15.

[3]

N. Atzpadin, P. Kauff, and O. Schreer. Stereo analysis by hybrid recursive matching for real-time immersive video conferencing. IEEE Trans. Circuits and Systems for Video Technology, 14(3):321--334, Mar. 2004.

Digital Library

[4]

A. Bartoli. A random sampling strategy for piecewise planar scene segmentation. Computer Vision and Image Understanding, 105(1):42--59, 2007.

Digital Library

[5]

J.-Y. Bouguet. Camera calibration toolbox-matlab. http://www.vision.caltech.edu/bouguetj/calib_doc/. Accessed: 2014-02-15.

[6]

Y. Boykov, O. Veksler, and R. Zabih. Fast approximate energy minimization via graph cuts. IEEE Transactions on Pattern Analysis and Machine Intelligence, 23(11):1222--1239, 2001.

Digital Library

[7]

G. Bradski. Opencv library in c++. Dr. Dobb's Journal of Software Tools, 2000.

[8]

G. Bradski and A. Kaehler. Learning OpenCV: Computer vision with the OpenCV library. O'Reilly Media, Inc., 2008.

Digital Library

[9]

P.-L. Chang, D. Stoyanov, A. J. Davison, et al. Real-time dense stereo reconstruction using convex optimisation with a cost-volume for image-guided robotic surgery. In Medical Image Computing and Computer-Assisted Intervention, pages 42--49. 2013.

[10]

F. D. Fabien Mourgues and E. Coste-Maniere. 3d reconstruction of the operating field for image overlay in 3d-endoscopic surgery. In Proceedings. IEEE and ACM International Symposium on Augmented Reality, 2001., pages 191--192, 2001.

Digital Library

[11]

G. S. Guthart and J. K. Salisbury. The intuitive telesurgery system: overview and application. In Proceedings of the IEEE international conference on robotics and automation, pages 618--621, 2000.

[12]

R. Hartley and A. Zisserman. Multiple view geometry in computer vision. Cambridge university press, 2003.

Digital Library

[13]

R. I. Hartley and P. Sturm. Triangulation. Computer vision and image understanding, 68(2):146--157, 1997.

Digital Library

[14]

H. Hirschmuller. Stereo processing by semiglobal matching and mutual information. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(2):328--341, 2008.

Digital Library

[15]

A. Karargyris and N. Bourbakis. Three-dimensional reconstruction of the digestive wall in capsule endoscopy videos using elastic video interpolation. IEEE Transactions on Medical Imaging, 30(4):957--971, 2011.

[16]

K. Konolige. Realtime stereo and motion analysis on passive video images using an efficient image-to-image comparison algorithm requiring minimal buffering, 2007. US Patent 7, 194, 126.

[17]

C. T. Loop and Z. Zhang. Computing rectifying homographies for stereo vision. In CVPR'99, pages 1125--1131, 1999.

[18]

L. Maier-Hein, P. Mountney, A. Bartoli, H. Elhawary, D. Elson, A. Groch, A. Kolb, M. Rodrigues, J. Sorger, S. Speidel, et al. Optical techniques for 3d surface reconstruction in computer-assisted laparoscopic surgery. Medical image analysis, 17(8):974--996, 2013.

[19]

D. J. Mirota, M. Ishii, and G. D. Hager. Vision-based navigation in image-guided interventions. Annual review of biomedical engineering, 13: 297--319, 2011.

[20]

P. Mountney, D. Stoyanov, and G.-Z. Yang. Three-dimensional tissue deformation recovery and tracking. Signal Processing Magazine, IEEE, 27(4):14--24, 2010.

[21]

M. Pollefeys, D. Nistér, J.-M. Frahm, A. Akbarzadeh, P. Mordohai, B. Clipp, C. Engels, D. Gallup, S.-J. Kim, P. Merrell, et al. Detailed real-time urban 3d reconstruction from video. International Journal of Computer Vision, 78(2-3):143--167, 2008.

Digital Library

[22]

G. Puerto-Souza and G. Mariottini. A fast and accurate feature-matching algorithm for minimally-invasive endoscopic images. 2013.

[23]

S. Roehl, S. Bodenstedt, S. Suwelack, H. Kenngott, B. P. Müller-Stich, R. Dillmann, and S. Speidel. Dense gpu-enhanced surface reconstruction from stereo endoscopic images for intraoperative registration. Medical physics, 39(3):1632--1645, 2012.

[24]

D. Stoyanov. Surgical vision. Annals of Biomedical Engineering, 40(2):332--345, 2012.

[25]

D. Stoyanov, D. Elson, and G.-Z. Yang. Illumination position estimation for 3d soft-tissue reconstruction in robotic minimally invasive surgery. In Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on, pages 2628--2633. IEEE, 2009.

Digital Library

[26]

D. Stoyanov, M. V. Scarzanella, P. Pratt, and G.-Z. Yang. Real-time stereo reconstruction in robotically assisted minimally invasive surgery. In Proceedings of the 13th International Conference on Medical Image Computing and Computer-assisted Intervention: Part I, MICCAI'10, pages 275--282, Berlin, Heidelberg, 2010. Springer-Verlag.

Digital Library

[27]

D. Stoyanov, M. V. Scarzanella, P. Pratt, and G.-Z. Yang. Real-time stereo reconstruction in robotically assisted minimally invasive surgery. In Medical Image Computing and Computer-Assisted Intervention--MICCAI 2010, pages 275--282. Springer, 2010.

Digital Library

[28]

C. Tomasi and R. Manduchi. Bilateral filtering for gray and color images. In Computer Vision, 1998. Sixth International Conference on, pages 839--846. IEEE, 1998.

Digital Library

[29]

J. Totz, P. Mountney, D. Stoyanov, and G.-Z. Yang. Dense surface reconstruction for enhanced navigation in mis. In Medical Image Computing and Computer-Assisted Intervention--MICCAI 2011, pages 89--96. Springer, 2011.

Digital Library

[30]

M. Visentini-Scarzanella, G. P. Mylonas, D. Stoyanov, and G.-Z. Yang. i-brush: A gaze-contingent virtual paintbrush for dense 3d reconstruction in robotic assisted surgery. In Medical Image Computing and Computer-Assisted Intervention--MICCAI 2009, pages 353--360. Springer, 2009.

Digital Library

[31]

E. Vural and A. A. Alatan. Outlier removal for sparse 3d reconstruction from video. In 3DTV Conference: The True Vision-Capture, Transmission and Display of 3D Video, 2008, pages 341--344. IEEE, 2008.

[32]

T. Werner and A. Zisserman. New techniques for automated architectural reconstruction from photographs. In Computer Vision---ECCV 2002, pages 541--555. Springer, 2002.

Digital Library

[33]

Z. Zhang. A flexible new technique for camera calibration. IEEE Trans. Pattern Anal. Mach. Intell., 22(11):1330--1334, Nov. 2000.

Digital Library

Cited By

Xu ZHaroutunian MMurphy ANeasham JNorman R(2022)An Integrated Visual Odometry System With Stereo Camera for Unmanned Underwater VehiclesIEEE Access10.1109/ACCESS.2022.318703210(71329-71343)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3187032
Münzer BSchoeffmann KBöszörmenyi L(2018)Content-based processing and analysis of endoscopic images and videosMultimedia Tools and Applications10.1007/s11042-016-4219-z77:1(1323-1362)Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.1007/s11042-016-4219-z
Parchami MCadeddu JMariottini G(2014)Endoscopic stereo reconstruction: A comparative study2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society10.1109/EMBC.2014.6944115(2440-2443)Online publication date: Aug-2014
https://doi.org/10.1109/EMBC.2014.6944115

Index Terms

A comparative study on 3-D stereo reconstruction from endoscopic images
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision tasks
        Scene understanding

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cover image ACM Other conferences

PETRA '14: Proceedings of the 7th International Conference on PErvasive Technologies Related to Assistive Environments

May 2014

408 pages

ISBN:9781450327466

DOI:10.1145/2674396

Conference Chair:
Fillia Makedon
University of Texas at Arlington
,
Program Chairs:
Mark Clements
Georgia Institute of Technology
,
Catherine Pelachaud
TELECOM ParisTech, France
,
Vana Kalogeraki
Athens University of Economics and Bus
,
Ilias Maglogiannis
University of Piraeus, Greece

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

iPerform Center: iPerform Center for Assistive Technologies to Enhance Human Performance
CSE@UTA: Department of Computer Science and Engineering, The University of Texas at Arlington
HERACLEIA: HERACLEIA Human-Centered Computing Laboratory at UTA
U of Tex at Arlington: U of Tex at Arlington
NCRS: Demokritos National Center for Scientific Research
Fulbrigh, Greece: Fulbright Foundation, Greece

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 May 2014

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PETRA '14

Sponsor:

iPerform Center
CSE@UTA
HERACLEIA
U of Tex at Arlington
NCRS
Fulbrigh, Greece

PETRA '14: The 7th International Conference on PErvasive Technologies Related to Assistive Environments

May 27 - 30, 2014

Rhodes, Greece

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Cited By

Xu ZHaroutunian MMurphy ANeasham JNorman R(2022)An Integrated Visual Odometry System With Stereo Camera for Unmanned Underwater VehiclesIEEE Access10.1109/ACCESS.2022.318703210(71329-71343)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3187032
Münzer BSchoeffmann KBöszörmenyi L(2018)Content-based processing and analysis of endoscopic images and videosMultimedia Tools and Applications10.1007/s11042-016-4219-z77:1(1323-1362)Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.1007/s11042-016-4219-z
Parchami MCadeddu JMariottini G(2014)Endoscopic stereo reconstruction: A comparative study2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society10.1109/EMBC.2014.6944115(2440-2443)Online publication date: Aug-2014
https://doi.org/10.1109/EMBC.2014.6944115

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