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Título
Anisotropic Diffusion Filter with Memory based on Speckle Statistics for Ultrasound Images
Autor
Año del Documento
2015
Documento Fuente
IEEE Trans. on Image Processing, Vol. 24, No. 1, Enero 2015
Resumen
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
Idioma
spa
Derechos
openAccess
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