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Morphological Scheme for Morphometric Analysis of Epidermal Biopsy Images

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Mathematical Morphology and Its Applications to Image Processing

Part of the book series: Computational Imaging and Vision ((CIVI,volume 2))

Abstract

This paper addresses the problem of morphometric analysis of microscope images from cutaneous biopsy samples. A morphological scheme is applied for the automatic measurement of histologic parameters of the epidermis. It consists in an unsupervised segmentation approach that is strongly based on an ‘a priori’ model of the images. The watershed algorithm has proven to be a very powerful tool for the introduction of such ‘a priori’ information, because the segmentation process can be conveniently guided by some strategic markers in order to perform the detection of the desired structures. This permits an automatic measurement of some objective parameters which are highly correlated with the evolution of some skin diseases.

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References

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Author information

Authors and Affiliations

  1. Dept. de Teoria del Senyal i Comunicacions, Universitat Politecnica de Catalunya, Apdo. 30 002, 08071, Barcelona, Spain

    J. R. Casas & P. Esteban

  2. Servei d’Anatomia Patologica, Ciutat Sanitaria de Bellvitge, Feixa Llarga s/n, 08907, L’Hosp. de Llobregat, Spain

    A. Moreno & M. Carrera

Authors
  1. J. R. Casas
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  2. P. Esteban
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  3. A. Moreno
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  4. M. Carrera
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Editor information

Editors and Affiliations

  1. Centre de Morphologie Mathématique, Ecole des Mines de Paris, Fontainebleau, France

    Jean Serra  & Pierre Soille  & 

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© 1994 Springer Science+Business Media Dordrecht

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Casas, J.R., Esteban, P., Moreno, A., Carrera, M. (1994). Morphological Scheme for Morphometric Analysis of Epidermal Biopsy Images. In: Serra, J., Soille, P. (eds) Mathematical Morphology and Its Applications to Image Processing. Computational Imaging and Vision, vol 2. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-1040-2_42

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  • DOI: https://doi.org/10.1007/978-94-011-1040-2_42

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-010-4453-0

  • Online ISBN: 978-94-011-1040-2

  • eBook Packages: Springer Book Archive

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