Literature DB >> 24554292

Speckle suppressing anisotropic diffusion filter for medical ultrasound images.

Saraniya Ovireddy1, Ezhilarasi Muthusamy.   

Abstract

Ultrasonography is often preferred over the other medical imaging modalities due to its noninvasive nature, cost-effectiveness, and portability. However, the resolution of the ultrasound image greatly depends upon the presence of speckle noise. Speckle noise generally tends to reduce the image resolution and contrast, thereby reducing the diagnostic resolution of this imaging modality. In this paper, we propose a speckle suppressing anisotropic diffusion (SSAD) filter, to remove the speckle noise from B-Mode Ultrasound images. The performance of the SSAD filter is compared with the existing diffusion filters. The evaluation is based on their application to images simulated by Field II (developed by Jensen et al.). The algorithms were also tested for clinical ultrasound images of polycystic ovaries obtained from HDI 5000 Ultrasound Scanner. Performance evaluation was done by both numerical and functional parameters. The proposed filter yields better results in terms of greatest structural similarity index map (SSIM) of 0.95 and accuracy of 99.5.

Entities:  

Keywords:  anisotropic diffusion; speckle suppression anisotropic diffusion filter; ultrasonography

Mesh:

Year:  2014        PMID: 24554292     DOI: 10.1177/0161734613512200

Source DB:  PubMed          Journal:  Ultrason Imaging        ISSN: 0161-7346            Impact factor:   1.578


  2 in total

1.  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

2.  De-Speckling Breast Cancer Ultrasound Images Using a Rotationally Invariant Block Matching Based Non-Local Means (RIBM-NLM) Method.

Authors:  Gelan Ayana; Kokeb Dese; Hakkins Raj; Janarthanan Krishnamoorthy; Timothy Kwa
Journal:  Diagnostics (Basel)       Date:  2022-03-30
  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.