Articles producció científica> Enginyeria Informàtica i Matemàtiques

A probabilistic approach for breast boundary extraction in mammograms

  • Datos identificativos

    Identificador: PC:540
    Handle: http://hdl.handle.net/20.500.11797/PC540
  • Autores:

    Aghdam, H.H.
    Puig, D.
    Solanas, A.
  • Otros:

    Autor según el artículo: Aghdam, H.H. Puig, D. Solanas, A.
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    Enlace a la fuente original: http://www.hindawi.com/journals/cmmm/2013/408595/
    Departamento: Enginyeria Informàtica i Matemàtiques
    DOI del artículo: 10.1155/2013/408595
    Resumen: The extraction of the breast boundary is crucial to perform further analysis of mammogram. Methods to extract the breast boundary can be classified into two categories: methods based on image processing techniques and those based on models. The former use image transformation techniques such as thresholding, morphological operations, and region growing. In the second category, the boundary is extracted using more advanced techniques, such as the active contour model. The problem with thresholding methods is that it is a hard to automatically find the optimal threshold value by using histogram information. On the other hand, active contour models require defining a starting point close to the actual boundary to be able to successfully extract the boundary. In this paper, we propose a probabilistic approach to address the aforementioned problems. In our approach we use local binary patterns to describe the texture around each pixel. In addition, the smoothness of the boundary is handled by using a new probability model. Experimental results show that the proposed method reaches 38% and 50% improvement with respect to the results obtained by the active contour model and threshold-based methods respectively, and it increases the stability of the boundary extraction process up to 86%.
    Entidad: Universitat Rovira i Virgili.
    Áreas temáticas: Mammography
    Año de publicación de la revista: 2013
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    ISSN: 1748-6718
    Volumen de revista: 2013