Speckle reducing anisotropic diffusion

By Yongjian Yu, Scott Thomas Acton. IEEE Transactions on Image Processing, 2002

2,009 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/631e591c285691ed134a497d1f41834c16d78d4f

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In Biomedical Engineering

In Computer Vision and Pattern Recognition

In Radiology, Nuclear Medicine and Imaging

Citations in the corpus

A Tutorial on Speckle Reduction in Synthetic Aperture Radar Images (2013, methodology): “Another index of edge preservation is Pratt’s figure of merit (FOM), which has been used in [96] for the quality assessment of despeckled SAR and ultrasound images.”
Automated 3-D Intraretinal Layer Segmentation of Macular Spectral-Domain Optical Coherence Tomography Images (2009, neutral): “After applying a speckle-reducing anisotropic diffusion method [22], the surfaces on the flattened and truncated volumetric spectral images were segmented in two groups: surfaces 1, 6, and 7 were segmented simultaneously, followed by the”
Oriented Speckle Reducing Anisotropic Diffusion (2007, methodology): “As proposed by [16], we use the Canny edge detector [43] with a standard deviation of 0.”
Comparative evaluation of despeckle filtering in ultrasound imaging of the carotid artery (2005, methodology): “Early attempts to suppress speckle noise were implemented by averaging of uncorrelated images of the same tissue recorded under different spatial positions [5], [9], [10].”
Automated breast cancer detection and classification using ultrasound images: A survey (2015, background): “[45] proposed a directional adaptive mean filter based on 2D texture homogeneity histogram to suppress speckles in ultrasound images.”
Ultrasound image segmentation: a survey (2006, methodology): “In the second stage, a Speckle Reducing Anisotropic Diffusion, (SRAD [113]), was applied to enhance the images and the instantaneous coefﬁcient of variation (ICOV) was utilized as an edge cue in the derivation of the external energy of the active contour model.”
On the estimation of the coefficient of variation for anisotropic diffusion speckle filtering (2006, methodology): “Recently, Yu and Acton [6] have proposed a novel filtering scheme based on the filters first described by Lee and Frost.”
Removing Multiplicative Noise by Douglas-Rachford Splitting Methods (2010, methodology): “Beyond variational approaches there exist other techniques to remove multiplicative noise, e.g., local linear minimum mean square error approaches [46, 47] or anisotropic diffusion methods [1, 44, 66] which will not be addressed in this paper.”
Intraretinal Layer Segmentation of Macular Optical Coherence Tomography Images Using Optimal 3-D Graph Search (2008, neutral): “As a preprocessing step, a specklereducing anisotropic diffusion method [19] was applied (Fig.”
Automated Breast Ultrasound Lesions Detection Using Convolutional Neural Networks (2018, methodology): “In addition, the iteration time t was set to 50 in the speckle reducing anisotropic diffusion (SRAD) process.”
A performance study of general-purpose applications on graphics processors using CUDA (2008, background): “as speckles, without destroying important image features [31].”
Active Contour External Force Using Vector Field Convolution for Image Segmentation (2007, methodology): “Speckle reducing anisotropic diffusion (SRAD) is employed to suppress the noise [35].”
Comparison of Filters used for Underwater Image Pre-Processing (2010, methodology): “Perona and Malik[1] anisotropic diffusion is the edge sensitive extension of the average filter.”