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A Windows-Based User Friendly System for Image Analysis with Partial Differential Equations

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Scale-Space Theories in Computer Vision (Scale-Space 1999)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1682))

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Abstract

In this paper we present and briefly describe a Windows user- friendly system designed to assist with the analysis of images in general, and biomedical images in particular. The system, which is being made publicly available to the research community, implements basic 2D image analysis operations based on partial differential equations (PDE’s). The system is under continuous development, and already includes a large number of image enhancement and segmentation routines that have been tested for several applications.

This work was supported by a grant from the Offce of Naval Research ONR-N0001497-1-0509, the Offce of Naval Research Young Investigator Award, the Presidential Early Career Awards for Scientists and Engineers (PECASE), the National Science Foundation CAREER Award, and the National Science Foundation Learning and Intelligent Systems Program (LIS).

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References

  1. L. Alvarez, P. L. Lions, and J. M. Morel, “Image selective smoothing and edge detection by nonlinear diffusion,” SIAM J. Numer. Anal. 29, pp. 845–866, 1992.

    Article  MATH  MathSciNet  Google Scholar 

  2. M. Bertalmio, G. Sapiro, and G. Randall, “Morphing active contours: A geometric, topology-free, technique for image segmentation and tracking,” Proc. IEEE ICIP, Chicago, October 1998.

    Google Scholar 

  3. M. Black, G. Sapiro, D. Marimont, and D. Heeger, “Robust anisotropic diffusion,” IEEE Trans. Image Processing, March 1998.

    Google Scholar 

  4. V. Caselles, R. Kimmel, and G. Sapiro, “Geodesic active contours,” Proc. Int. Conf. Comp. Vision’ 95, Cambridge, June 1995.

    Google Scholar 

  5. V. Caselles, R. Kimmel, and G. Sapiro, “Geodesic active contours,” International Journal of Computer Vision 22:1, pp. 61–79, 1997.

    Article  MATH  Google Scholar 

  6. V. Caselles, G. Sapiro, and D. H. Chung, “Vector median filters, inf-sup operations, and coupled PDE’s: Theoretical connections,” ECE-University of Minnesota Technical Report, September 1998.

    Google Scholar 

  7. L. Cohen and R. Kimmel, “Global minimum for active contours models: A minimal path approach,” Int. J. of Computer Vision 24, pp. 57–78, 1997.

    Article  Google Scholar 

  8. M. Kass, A. Witkin, and D. Terzopoulos, “Snakes: Active contour models,” International Journal of Computer Vision 1, pp. 321–331, 1988.

    Article  Google Scholar 

  9. R. Kimmel and J. A. Sethian, “Fast marching method for computation of distance maps,” LBNL Report 38451, UC Berkeley, February, 1996

    Google Scholar 

  10. S. Kichenassamy, A. Kumar, P. Olver, A. Tannenbaum, and A. Yezzi, “Conformal curvature flows: from phase transitions to active vision,” Archive for Rational Mechanics and Analysis 134, pp. 275–301, 1996.

    Article  MATH  MathSciNet  Google Scholar 

  11. R. Malladi, J. A. Sethian and B. C. Vemuri, “Shape modeling with front propagation: A level set approach,” IEEE-PAMI 17, pp. 158–175, 1995.

    Google Scholar 

  12. S. J. Osher and J. A. Sethian, “Fronts propagation with curvature dependent speed: Algorithms based on Hamilton-Jacobi formulations,” Journal of Computational Physics 79, pp. 12–49, 1988.

    Article  MATH  MathSciNet  Google Scholar 

  13. P. Perona and J. Malik, “Scale-space and edge detection using anisotropic diffusion,” IEEE-PAMI 12, pp. 629–639, 1990.

    Google Scholar 

  14. G. Sapiro, “Color snakes,” Computer Vision and Image Understanding 68:2, pp. 247–253, 1997.

    Article  MathSciNet  Google Scholar 

  15. J. Sethian, Level Set Methods: Evolving Interfaces in Geometry, Fluid Mechanics, Computer Vision and Materials Sciences, Cambridge University Press, Cambridge-UK, 1996.

    Google Scholar 

  16. J. Shah, “Recovery of shapes by evolution of zero-crossings,” Technical Report, Math. Dept. Northeastern Univ. Boston MA, 1995.

    Google Scholar 

  17. D. Terzopoulos, A. Witkin, and M. Kass, “Constraints on deformable models: Recovering 3D shape and nonrigid motions,” AI 36, 1988.

    Google Scholar 

  18. J. N. Tsitsiklis, “Efficient algorithms for globally optimal trajectories,” IEEE Transactions on Automatic Control 40 pp. 1528–1538, 1995.

    Article  MATH  MathSciNet  Google Scholar 

  19. L. Vazquez, G. Sapiro, and G. Randall, “Segmenting neurons in electronic microscopy via geometric tracing,” Proc. IEEE ICIP, Chicago, October 1998.

    Google Scholar 

  20. J. Weickert, “Coherence-enhancing diffusion of color images,” Proc. VII National Symp. on Pattern Recognition and Image Analysis, pp. 239–244, Barcelona, Spain, 1997.

    Google Scholar 

  21. R. T. Whitaker, “Algorithms for implicit deformable models,” Proc. ICCV’95, pp. 822–827, Cambridge, June 1995.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, 55455

    Do Hyun Chung & Guillermo Sapiro

Authors
  1. Do Hyun Chung
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  2. Guillermo Sapiro
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Editor information

Editors and Affiliations

  1. The IT University in Copenhagen, Glentevej 67, DK-2400, Copenhagen NV, Denmark

    Mads Nielsen

  2. Department of Computer Science, University of Copenhagen, Universitetsparken 1, DK-2100, Copenhagen OE, Denmark

    Peter Johansen  & Ole Fogh Olsen  & 

  3. Department of Mathematics and Computer Science, University of Mannheim, D-68131, Mannheim, Germany

    Joachim Weickert

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© 1999 Springer-Verlag Berlin Heidelberg

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Chung, D.H., Sapiro, G. (1999). A Windows-Based User Friendly System for Image Analysis with Partial Differential Equations. In: Nielsen, M., Johansen, P., Olsen, O.F., Weickert, J. (eds) Scale-Space Theories in Computer Vision. Scale-Space 1999. Lecture Notes in Computer Science, vol 1682. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48236-9_42

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  • DOI: https://doi.org/10.1007/3-540-48236-9_42

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66498-7

  • Online ISBN: 978-3-540-48236-9

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