Literature DB >> 16948314

On the estimation of the coefficient of variation for anisotropic diffusion speckle filtering.

Santiago Aja-Fernández1, Carlos Alberola-López.   

Abstract

In this paper, we focus on the problem of speckle removal by means of anisotropic diffusion and, specifically, on the importance of the correct estimation of the statistics involved. First, we derive an anisotropic diffusion filter that does not depend on a linear approximation of the speckle model assumed, which is the case of a previously reported filter, namely, SRAD. Then, we focus on the problem of estimation of the coefficient of variation of both signal and noise and of noise itself. Our experiments indicate that neighborhoods used for parameter estimation do not need to coincide with those used in the diffusion equations. Then, we show that, as long as the estimates are good enough, the filter proposed here and the SRAD perform fairly closely, a fact that emphasizes the importance of the correct estimation of the coefficients of variation.

Mesh:

Year:  2006        PMID: 16948314     DOI: 10.1109/tip.2006.877360

Source DB:  PubMed          Journal:  IEEE Trans Image Process        ISSN: 1057-7149            Impact factor:   10.856


  19 in total

1.  Enhancement of the ultrasound images by modified anisotropic diffusion method.

Authors:  Deepti Mittal; Vinod Kumar; Suresh Chandra Saxena; Niranjan Khandelwal; Naveen Kalra
Journal:  Med Biol Eng Comput       Date:  2010-06-24       Impact factor: 2.602

2.  Denoising of Ultrasound Cervix Image Using Improved Anisotropic Diffusion Filter.

Authors:  R Jemila Rose; S Allwin
Journal:  West Indian Med J       Date:  2015-05-13       Impact factor: 0.171

3.  Assessment of image features for vessel wall segmentation in intravascular ultrasound images.

Authors:  Lucas Lo Vercio; José Ignacio Orlando; Mariana Del Fresno; Ignacio Larrabide
Journal:  Int J Comput Assist Radiol Surg       Date:  2016-01-25       Impact factor: 2.924

4.  Stochastic speckle noise compensation in optical coherence tomography using non-stationary spline-based speckle noise modelling.

Authors:  Andrew Cameron; Dorothy Lui; Ameneh Boroomand; Jeffrey Glaister; Alexander Wong; Kostadinka Bizheva
Journal:  Biomed Opt Express       Date:  2013-08-28       Impact factor: 3.732

5.  Variability of waiting times for the 4 most prevalent cancer types in Ontario: a retrospective population-based analysis.

Authors:  Amir Rastpour; Mehmet A Begen; Alexander V Louie; Gregory S Zaric
Journal:  CMAJ Open       Date:  2018-06-07

6.  Ultrasound speckle reduction based on fractional order differentiation.

Authors:  Dangguo Shao; Ting Zhou; Fan Liu; Sanli Yi; Yan Xiang; Lei Ma; Xin Xiong; Jianfeng He
Journal:  J Med Ultrason (2001)       Date:  2016-12-23       Impact factor: 1.314

7.  Automatic segmentation of coronary morphology using transmittance-based lumen intensity-enhanced intravascular optical coherence tomography images and applying a localized level-set-based active contour method.

Authors:  Shiju Joseph; Asif Adnan; David Adlam
Journal:  J Med Imaging (Bellingham)       Date:  2016-11-29

8.  A Multi Directional Perfect Reconstruction Filter Bank Designed with 2-D Eigenfilter Approach: Application to Ultrasound Speckle Reduction.

Authors:  Mukund B Nagare; Bhushan D Patil; Raghunath S Holambe
Journal:  J Med Syst       Date:  2016-12-29       Impact factor: 4.460

9.  An Automated Framework for Large Scale Retrospective Analysis of Ultrasound Images.

Authors:  Pradeeba Sridar; Ashnil Kumar; Ann Quinton; Narelle June Kennedy; Ralph Nanan; Jinman Kim
Journal:  IEEE J Transl Eng Health Med       Date:  2019-11-19       Impact factor: 3.316

10.  SVM-Based CAC System for B-Mode Kidney Ultrasound Images.

Authors:  M B Subramanya; Vinod Kumar; Shaktidev Mukherjee; Manju Saini
Journal:  J Digit Imaging       Date:  2015-08       Impact factor: 4.056

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