LIVER SEGMENTATION USING LEVEL SETS AND GENETIC ALGORITHMS

Dário A. B. Oliveira, Raul Q. Feitosa, Mauro M. Correia

2009

Abstract

This paper presents a method based on level sets to segment the liver using Computer Tomography (CT) images. Initially, the liver boundary is manually set in one slice as an initial solution, and then the method automatically segments the liver in all other slices, sequentially. In each step of iteration it fits a Gaussian curve to the liver histogram to model the speed image in which the level sets propagates. The parameters of our method were estimated using Genetic Algorithms (GA) and a database of reference segmentations. The method was tested using 20 different exams and five different measures of performance, and the results obtained confirm the potential of the method. The cases in which the method presented a poor performance are also discussed in order to instigate further research.

References

  1. Davis L. Handbook of Genetic Algorithms. Van Nostrand Reinhold Company, New York, 1990.
  2. Fujimoto H., Gu L., and Kaneko T., “Recognition of abdominal organs using 3D mathematical morphology,” Trans. Inst. Electron. Inf. Commun. Eng. D-II, no. 5, pp. 843-850, May 2001.
  3. Heimann T.; van Ginneken B.; Styner M.. "3D Segmentation in the Clinic: A Grand Challenge", (Eds.): 3D Segmentation in the Clinic: A Grand Challenge, pp. 7-15, 2007.
  4. Malladi, R. ,Sethian, J.A., Vemuri, B.C.. Shape modeling with front propagation: a level set approach. IEEE rans. Pattern Anal. Mach. Intell. 17 (2) 158-175, 1995.
  5. Michalewicz Z (1994) Genetic Algorithms + Data Structures = Evolution Pro-grams. Springer-Verlag, Berlin Heidelberg New York
  6. Lamecker H., Zachow S., Haberl H., Stiller M.. Medical Applications for Statistical 3D Shape Models. Proc. Computer Aided Surgery Around the Head, volume 17 of Fortschritt- Berichte VDI, p. 61, 2005.
  7. Osher S., Sethian J. Fronts propagating with curvaturedependent speed: algorithms based on HamiltonJacobi formulations. J. Comput. Phys. 79 (1998) 12- 49.
  8. Yoo T.S., Ackerman M. J., Lorensen W. E., Schroeder W., Chalana V., Aylward S., Metaxes D., Whitaker R.. Engineering and Algorithm Design for an Image Processing API: A Technical Report on ITK - The Insight Toolkit. In Proc. of Medicine Meets Virtual Reality, J. Westwood, ed., IOS Press Amsterdam pp 586-592 (2002).
Download


Paper Citation


in Harvard Style

A. B. Oliveira D., Q. Feitosa R. and M. Correia M. (2009). LIVER SEGMENTATION USING LEVEL SETS AND GENETIC ALGORITHMS . In Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2009) ISBN 978-989-8111-69-2, pages 154-159. DOI: 10.5220/0001787401540159


in Bibtex Style

@conference{visapp09,
author={Dário A. B. Oliveira and Raul Q. Feitosa and Mauro M. Correia},
title={LIVER SEGMENTATION USING LEVEL SETS AND GENETIC ALGORITHMS},
booktitle={Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2009)},
year={2009},
pages={154-159},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001787401540159},
isbn={978-989-8111-69-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2009)
TI - LIVER SEGMENTATION USING LEVEL SETS AND GENETIC ALGORITHMS
SN - 978-989-8111-69-2
AU - A. B. Oliveira D.
AU - Q. Feitosa R.
AU - M. Correia M.
PY - 2009
SP - 154
EP - 159
DO - 10.5220/0001787401540159