Local Statistics-based Speckle Reducing Bilateral Filter for Medical Ultrasound Images

2020 ◽  
Vol 25 (6) ◽  
pp. 2367-2389
Author(s):  
Karamjeet Singh ◽  
Bhisham Sharma ◽  
Jaiteg Singh ◽  
Gautam Srivastava ◽  
Suchita Sharma ◽  
...  
Keyword(s):  
Bilateral Filter ◽  
Ultrasound Images ◽  
Medical Ultrasound ◽  
Local Statistics

scholarly journals Denoising of Medical Ultrasound Images using Wavelet Transform with Bilateral Filter

2019 ◽  
Vol 8 (4) ◽  
pp. 8113-8116
Keyword(s):  
Wavelet Transform ◽  
Bilateral Filter ◽  
Intrinsic Noise ◽  
Speckle Noise ◽  
Computer Assisted ◽  
Ultrasound Images ◽  
Medical Ultrasound ◽  
Edge Preservation ◽  
Neighborhood Relationship ◽  
Speckle Filtering

Medical image degradation contains a significant impact on image quality and therefore affects the human interpretation and also the accuracy of computer assisted diagnostics techniques, unfortunately ultrasound images are principally degraded by an intrinsic noise known as speckle noise. Therefore, de- speckle filtering may be pre-processing step in medical ultrasound images. During this paper we propose a new image de-noising technique is the combination of bilateral filter and wavelet transform. The main contribution of this paper is within the use of a new neighborhood relationship to develop a new multi-scale bilateral filter. Experimental outcomes validate the usefulness and also the correctness of the proposed filter in edge preservation and speckle noise reduction for medical ultrasound images.

Wavelet and fast bilateral filter based de-speckling method for medical ultrasound images

2015 ◽  
Vol 18 ◽  
pp. 1-10 ◽  
Author(s):  
Ju Zhang ◽  
Guangkuo Lin ◽  
Lili Wu ◽  
Chen Wang ◽  
Yun Cheng
Keyword(s):  
Bilateral Filter ◽  
Ultrasound Images ◽  
Medical Ultrasound

scholarly journals Motion blur invariant for estimating motion parameters of medical ultrasound images

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Barmak Honarvar Shakibaei Asli ◽  
Yifan Zhao ◽  
John Ahmet Erkoyuncu
Keyword(s):  
Image Quality Assessment ◽  
Medical Image Analysis ◽  
Main Idea ◽  
Delta Function ◽  
Motion Blur ◽  
Ultrasound Images ◽  
Medical Ultrasound ◽  
Fetal Ultrasound ◽  
Dirac Delta ◽  
Motion Parameters

AbstractHigh-quality medical ultrasound imaging is definitely concerning motion blur, while medical image analysis requires motionless and accurate data acquired by sonographers. The main idea of this paper is to establish some motion blur invariant in both frequency and moment domain to estimate the motion parameters of ultrasound images. We propose a discrete model of point spread function of motion blur convolution based on the Dirac delta function to simplify the analysis of motion invariant in frequency and moment domain. This model paves the way for estimating the motion angle and length in terms of the proposed invariant features. In this research, the performance of the proposed schemes is compared with other state-of-the-art existing methods of image deblurring. The experimental study performs using fetal phantom images and clinical fetal ultrasound images as well as breast scans. Moreover, to validate the accuracy of the proposed experimental framework, we apply two image quality assessment methods as no-reference and full-reference to show the robustness of the proposed algorithms compared to the well-known approaches.

A Novel Despeckling Method for Medical Ultrasound Images Based on the Nonsubsampled Shearlet and Guided Filter

2019 ◽  
Vol 39 (3) ◽  
pp. 1449-1470 ◽  
Author(s):  
Ju Zhang ◽  
Xiaojie Xiu ◽  
Jun Zhou ◽  
Kailun Zhao ◽  
Zheng Tian ◽  
...  
Keyword(s):  
Guided Filter ◽  
Ultrasound Images ◽  
Medical Ultrasound
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