RT info:eu-repo/semantics/article
T1 Anisotropic Diffusion Filter with Memory based on Speckle Statistics for Ultrasound Images
A1 Ramos Llordén, Gabriel
A1 Vegas Sánchez-Ferrero, Gonzalo
A1 Martín Fernández, Marcos Antonio
A1 Alberola López, Carlos
A1 Aja Fernández, Santiago
K1 Ultrasound Imaging
K1 Speckle Filter
K1 Anisotropic Diffusion
K1 Memory Equations
K1 Volterra Equations
AB Ultrasound imaging exhibits considerable difficulties for medical visual inspection and for the development of automaticanalysis methods due to speckle, which negatively affects the perception of tissue boundaries and the performance of automaticsegmentation methods. With the aim of alleviating the effect of speckle, many filtering techniques are usually considered as apreprocessing step prior to automatic analysis methods or visual inspection. Most of the state-of-the-art filters try to reduce thespeckle effect without considering its relevance for the characterization of tissue nature. However, the speckle phenomenon is theinherent response of echo signals in tissues and can provide important features for clinical purposes. This loss of informationis even magnified due to the iterative process of some speckle filters, e.g., diffusion filters, which tend to produce over-filteringbecause of the progressive loss of relevant information for diagnostic purposes during the diffusion process. In this work, wepropose an anisotropic diffusion filter with a probabilistic-driven memory mechanism to overcome the over-filtering problem byfollowing a tissue selective philosophy. Specifically, we formulate the memory mechanism as a delay differential equation forthe diffusion tensor whose behavior depends on the statistics of the tissues, by accelerating the diffusion process in meaninglessregions and including the memory effect in regions where relevant details should be preserved. Results both in synthetic and realUS images support the inclusion of the probabilistic memory mechanism for maintaining clinical relevant structures, which areremoved by the state-of-the-art filters.
YR 2015
FD 2015
LK http://uvadoc.uva.es/handle/10324/15167
UL http://uvadoc.uva.es/handle/10324/15167
LA spa
NO IEEE Trans. on Image Processing, Vol. 24, No. 1, Enero 2015
DS UVaDOC
RD 26-dic-2024