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    Por favor, use este identificador para citar o enlazar este ítem:http://uvadoc.uva.es/handle/10324/15167

    Título
    Anisotropic Diffusion Filter with Memory based on Speckle Statistics for Ultrasound Images
    Autor
    Ramos Llordén, Gabriel
    Vegas Sánchez-Ferrero, Gonzalo
    Martín Fernández, Marcos AntonioAutoridad UVA Orcid
    Alberola López, CarlosAutoridad UVA Orcid
    Aja Fernández, SantiagoAutoridad UVA Orcid
    Año del Documento
    2015
    Documento Fuente
    IEEE Trans. on Image Processing, Vol. 24, No. 1, Enero 2015
    Zusammenfassung
    Ultrasound imaging exhibits considerable difficulties for medical visual inspection and for the development of automatic analysis methods due to speckle, which negatively affects the perception of tissue boundaries and the performance of automatic segmentation methods. With the aim of alleviating the effect of speckle, many filtering techniques are usually considered as a preprocessing step prior to automatic analysis methods or visual inspection. Most of the state-of-the-art filters try to reduce the speckle effect without considering its relevance for the characterization of tissue nature. However, the speckle phenomenon is the inherent response of echo signals in tissues and can provide important features for clinical purposes. This loss of information is even magnified due to the iterative process of some speckle filters, e.g., diffusion filters, which tend to produce over-filtering because of the progressive loss of relevant information for diagnostic purposes during the diffusion process. In this work, we propose an anisotropic diffusion filter with a probabilistic-driven memory mechanism to overcome the over-filtering problem by following a tissue selective philosophy. Specifically, we formulate the memory mechanism as a delay differential equation for the diffusion tensor whose behavior depends on the statistics of the tissues, by accelerating the diffusion process in meaningless regions and including the memory effect in regions where relevant details should be preserved. Results both in synthetic and real US images support the inclusion of the probabilistic memory mechanism for maintaining clinical relevant structures, which are removed by the state-of-the-art filters.
    Materias (normalizadas)
    Ultrasound Imaging
    Speckle Filter
    Anisotropic Diffusion
    Memory Equations
    Volterra Equations
    Revisión por pares
    SI
    DOI
    10.1109/TIP.2014.2371244
    Idioma
    spa
    URI
    http://uvadoc.uva.es/handle/10324/15167
    Derechos
    openAccess
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    • DEP71 - Artículos de revista [358]
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