Texture-Based Filtering and Front-Propagation Techniques for the Segmentation of Ultrasound Images

  • Miguel Alemán-Flores
  • Patricia Alemán-Flores
  • Luis Álvarez-León
  • M. Belén Esteban-Sánchez
  • Rafael Fuentes-Pavón
  • José M. Santana-Montesdeoca
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4739)


Ultrasound imaging segmentation is a common method used to help in the diagnosis in multiple medical disciplines. This medical image modality is particularly difficult to segment and analyze since the quality of the images is relatively low, because of the presence of speckle noise. In this paper we present a set of techniques, based on texture findings, to increase the quality of the images. We characterize the ultrasound image texture by a vector of responses to a set of Gabor filters. Also, we combine front-propagation and active contours segmentation methods to achieve a fast accurate segmentation with the minimal expert intervention.


Ultrasound Image Active Contour Image Texture Gabor Filter Gradient Magnitude 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Miguel Alemán-Flores
    • 1
  • Patricia Alemán-Flores
    • 2
  • Luis Álvarez-León
    • 1
  • M. Belén Esteban-Sánchez
    • 1
  • Rafael Fuentes-Pavón
    • 2
  • José M. Santana-Montesdeoca
    • 2
  1. 1.Departamento de Informática y Sistemas, Universidad de Las Palmas de Gran Canaria, 35017, Las PalmasSpain
  2. 2.Sección de Ecografía, Servicio de Radiodiagnóstico, Hospital Universitario Insular de Gran Canaria, 35016, Las PalmasSpain

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