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Adaptive Vision System for Segmentation of Echographic Medical Images Based on a Modified Mumford-Shah Functional

  • Conference paper
Advanced Concepts for Intelligent Vision Systems (ACIVS 2007)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4678))

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Abstract

This paper presents a novel adaptive vision system for accurate segmentation of tissue structures in echographic medical images. The proposed vision system incorporates a level-set deformable model based on a modified Mumford-Shah functional, which is estimated over sparse foreground and background regions in the image. This functional is designed so that it copes with the intensity inhomogeneity that characterizes echographic medical images. Moreover, a parameter tuning mechanism has been considered for the adaptation of the deformable model parameters. Experiments were conducted over a range of echographic images displaying abnormal structures of the breast and of the thyroid gland. The results show that the proposed adaptive vision system stands as an efficient, effective and nearly objective tool for segmentation of echographic images.

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Authors and Affiliations

  1. Dept. of Informatics and Telecommunications, University of Athens, Panepistimioupolis, 15784, Athens, Greece

    Dimitris K. Iakovidis, Michalis A. Savelonas & Dimitris Maroulis

Authors
  1. Dimitris K. Iakovidis
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  2. Michalis A. Savelonas
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  3. Dimitris Maroulis
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Editor information

Jacques Blanc-Talon Wilfried Philips Dan Popescu Paul Scheunders

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© 2007 Springer-Verlag Berlin Heidelberg

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Iakovidis, D.K., Savelonas, M.A., Maroulis, D. (2007). Adaptive Vision System for Segmentation of Echographic Medical Images Based on a Modified Mumford-Shah Functional. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2007. Lecture Notes in Computer Science, vol 4678. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74607-2_51

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  • DOI: https://doi.org/10.1007/978-3-540-74607-2_51

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74606-5

  • Online ISBN: 978-3-540-74607-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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