Literature DB >> 17491469

Oriented speckle reducing anisotropic diffusion.

Karl Krissian1, Carl-Fredrik Westin, Ron Kikinis, Kirby G Vosburgh.   

Abstract

Ultrasound imaging systems provide the clinician with noninvasive, low-cost, and real-time images that can help them in diagnosis, planning, and therapy. However, although the human eye is able to derive the meaningful information from these images, automatic processing is very difficult due to noise and artifacts present in the image. The speckle reducing anisotropic diffusion filter was recently proposed to adapt the anisotropic diffusion filter to the characteristics of the speckle noise present in the ultrasound images and to facilitate automatic processing of images. We analyze the properties of the numerical scheme associated with this filter, using a semi-explicit scheme. We then extend the filter to a matrix anisotropic diffusion, allowing different levels of filtering across the image contours and in the principal curvature directions. We also show a relation between the local directional variance of the image intensity and the local geometry of the image, which can justify the choice of the gradient and the principal curvature directions as a basis for the diffusion matrix. Finally, different filtering techniques are compared on a 2-D synthetic image with two different levels of multiplicative noise and on a 3-D synthetic image of a Y-junction, and the new filter is applied on a 3-D real ultrasound image of the liver.

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Year:  2007        PMID: 17491469     DOI: 10.1109/tip.2007.891803

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


  17 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

Review 2.  State-of-the-art in retinal optical coherence tomography image analysis.

Authors:  Ahmadreza Baghaie; Zeyun Yu; Roshan M D'Souza
Journal:  Quant Imaging Med Surg       Date:  2015-08

3.  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

4.  Nonlocal means-based speckle filtering for ultrasound images.

Authors:  Pierrick Coupé; Pierre Hellier; Charles Kervrann; Christian Barillot
Journal:  IEEE Trans Image Process       Date:  2009-05-27       Impact factor: 10.856

5.  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

6.  Ultrasonic image analysis and image-guided interventions.

Authors:  J Alison Noble; Nassir Navab; H Becher
Journal:  Interface Focus       Date:  2011-06-15       Impact factor: 3.906

7.  Entropy-based straight kernel filter for echocardiography image denoising.

Authors:  S Rajalaxmi; S Nirmala
Journal:  J Digit Imaging       Date:  2014-10       Impact factor: 4.056

8.  SUPRA: open-source software-defined ultrasound processing for real-time applications : A 2D and 3D pipeline from beamforming to B-mode.

Authors:  Rüdiger Göbl; Nassir Navab; Christoph Hennersperger
Journal:  Int J Comput Assist Radiol Surg       Date:  2018-03-28       Impact factor: 2.924

9.  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

10.  Phase asymmetry ultrasound despeckling with fractional anisotropic diffusion and total variation.

Authors:  Kunqiang Mei; Bin Hu; Baowei Fei; Binjie Qin
Journal:  IEEE Trans Image Process       Date:  2019-11-19       Impact factor: 10.856

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