Nonsubsampled contourlet transform with cross‐guided bilateral filter for despeckling of medical ultrasound images

2020 ◽  
Author(s):  
Thapasimuthan Joel ◽  
Rajagopal Sivakumar
Keyword(s):  
Bilateral Filter ◽  
Contourlet Transform ◽  
Ultrasound Images ◽  
Medical Ultrasound ◽  
Nonsubsampled Contourlet Transform

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.

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

Medical Ultrasound Image Denoising Algorithm Based on Nosubsampled Contourlet Transform

2014 ◽  
Vol 644-650 ◽  
pp. 3999-4004
Author(s):  
Min Fen Shen ◽  
Fei Huang ◽  
Zhi Fei Su ◽  
Li Sha Sun
Keyword(s):  
Clinical Medicine ◽  
Ultrasound Image ◽  
Contourlet Transform ◽  
Threshold Function ◽  
Ultrasound Images ◽  
Medical Ultrasound ◽  
Wavelet Thresholding ◽  
Scale Analysis ◽  
Multi Scale ◽  
Image Edge

Currently,the ultrasound image has been widely used in diagnosis and treatment of clinical medicine,the results obtained by the diagnostic accuracy and reliability of the image is directly related to the effects of diagnosis and treatment.Because ultrasound images in the imaging process inevitably contaminated noise,thus the research of inhibiting ultrasound image noise is one of the important issues in domestic and international ultrasound imaging techniques.This paper studies the multi-scale analysis and wavelet thresholding two theories,put forwarda denoising algorithm about combining the Nonsubsampling contourlet transform and a new threshold function,experiments show that the new algorithm can not only good at suppressing the noise of ultrasound images,and can better retain image edge and texture details.

Modeling of Log-Transformed Speckle Noise in the Contourlet Transform Domain for Medical Ultrasound Images

2014 ◽  
Vol 24 (02) ◽  
pp. 1540004 ◽  
Author(s):  
Shahriar Mahmud Kabir ◽  
Mohammed Imamul Hassan Bhuiyan
Keyword(s):  
Estimation Method ◽  
Speckle Noise ◽  
Diagnostic Value ◽  
Contourlet Transform ◽  
Speckle Reduction ◽  
Ultrasound Images ◽  
Medical Ultrasound ◽  
Transform Domain ◽  
Processing Step ◽  
Bessel K Form

Speckle noise in medical ultrasound (US) degrades the image quality and reduces its diagnostic value. Reduction of speckle noise is an important pre-processing step for the analysis and processing of medical ultrasound images. Knowledge of the statistics of the log-transformed speckle especially in the multi-resolution transform domain is important for developing effective homomorphic despeckling techniques, the most popular approach of speckle reduction from ultrasound images. In this paper, the bessel K-form (BKF) probability density function (pdf) is proposed as a highly suitable prior for modeling the log-transformed speckle noise in the well-known contourlet transform domain. A maximum likelihood based method is introduced for estimating the parameters of the BKF pdf. The effectiveness of the proposed estimation method is demonstrated using Monte Carlo simulations. The appropriateness of the BKF pdf in modeling the speckle is first studied extensively for simulated noise of different levels in the contourlet transform domain. Next, the suitability of BKF model is investigated for the case of real US images that include neonatal brain and breast tumors. It is shown that, in general the BKF prior can model the statistics of the contourlet transform coefficients corresponding to the log-transformed speckle better than the traditionally used Gaussian, normal inverse Gaussian and generalized Nakagami pdfs.

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
Sign in / Sign up

Export Citation Format

Share Document