scholarly journals Denoising Ultrasound Medical Images with Selective Fusion in Wavelet Domain

2015 ◽  
Vol 58 ◽  
pp. 129-139 ◽  
Author(s):  
P.V.V. Kishore ◽  
K.L. Mallika ◽  
M.V.D. Prasad ◽  
K.L. Narayana
Keyword(s):  
Medical Images ◽  
Wavelet Domain ◽  
Selective Fusion

The Combination of Adaptive Filters to Improve the Quality of Medical Images in New Wavelet Domain

2016 ◽  
pp. 46-76 ◽  
Author(s):  
Nguyen Thanh Binh ◽  
Vo Thi Hong Tuyet
Keyword(s):  
Medical Image ◽  
Adaptive Filters ◽  
Treatment Process ◽  
Medical Images ◽  
The Other ◽  
Diagnostic Process ◽  
Wavelet Domain ◽  
Medical Specialists ◽  
New Generation

Most of medical images not only have noise but also have blur. This problem reduces the quality of images and influences diagnostic process of medical specialists because a small detail in a medical image is very useful for treatment process. This chapter explores the new generation wavelets, which provides the basic framework for the development of adaptive techniques to improve the quality of medical images. The process of the method for improving medical images includes: decompose of medical images in nonsubsampled contourlet domain and calculate the coefficients of Bayesian thresholding combined with Lucy Richard to reconstruct the medical images. For demonstrating the superiority of the method, the results of the proposed method are compared with the results of the other methods in new generation wavelet domain.

The Combination of Adaptive Filters to Improve the Quality of Medical Images in New Wavelet Domain

2017 ◽  
pp. 1935-1966
Author(s):  
Nguyen Thanh Binh ◽  
Vo Thi Hong Tuyet
Keyword(s):  
Medical Image ◽  
Adaptive Filters ◽  
Treatment Process ◽  
Medical Images ◽  
The Other ◽  
Diagnostic Process ◽  
Wavelet Domain ◽  
Medical Specialists ◽  
New Generation

Most of medical images not only have noise but also have blur. This problem reduces the quality of images and influences diagnostic process of medical specialists because a small detail in a medical image is very useful for treatment process. This chapter explores the new generation wavelets, which provides the basic framework for the development of adaptive techniques to improve the quality of medical images. The process of the method for improving medical images includes: decompose of medical images in nonsubsampled contourlet domain and calculate the coefficients of Bayesian thresholding combined with Lucy Richard to reconstruct the medical images. For demonstrating the superiority of the method, the results of the proposed method are compared with the results of the other methods in new generation wavelet domain.

scholarly journals Noise-resistant Image Encryption Scheme for Medical Images in the Chaos and Wavelet Domain

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Arslan Shafique ◽  
Jameel Ahmed ◽  
Mujeeb Ur Rehman ◽  
Mohammad Mazyad Hazzazi
Keyword(s):  
Image Encryption ◽  
Medical Images ◽  
Encryption Scheme ◽  
Wavelet Domain

Intelligent reversible watermarking in integer wavelet domain for medical images

2012 ◽  
Vol 85 (4) ◽  
pp. 883-894 ◽  
Author(s):  
Muhammad Arsalan ◽  
Sana Ambreen Malik ◽  
Asifullah Khan
Keyword(s):  
Medical Images ◽  
Reversible Watermarking ◽  
Wavelet Domain ◽  
Integer Wavelet

GA-based multi-objective optimization technique for medical image denoising in wavelet domain

2021 ◽  
pp. 1-14
Author(s):  
Thavavel Vaiyapuri ◽  
Haya Alaskar ◽  
Zohra Sbai ◽  
Shri Devi
Keyword(s):  
Medical Image ◽  
Prior Information ◽  
Low Dose ◽  
Medical Images ◽  
Optimization Technique ◽  
Wavelet Domain ◽  
Multi Objective ◽  
Error Factor ◽  
The Brain

Medical images that are acquired with reduced radiation exposure or following the administration of imaging agents with a low dose, are often known to experience problems by the noise stemming from acquisition hardware as well as psychological sources. This noise can adversely affect the quality of diagnosis, but also prevent practitioners from computing quantitative functional information. With a view to overcoming these challenges, the current paper puts forward optimization of multi-objective for denoising medical images within the wavelet domain. This proposed technique entails the use of genetic algorithm (GA) to get the threshold optimized within the denoising framework of wavelets. Two purposes are associated with this technique: First, its ability to adapt with different noise types of noise in the image without requiring prior information about the imaging process per se. In addition, it balances relevant diagnostic details’ preservation against the reduction of noise by considering the optimization of the error factor of Liu and SNR as the foundation of objective function. According to the implementation of this method on magnetic resonance (MR) and ultrasound (US) images of the brain, a better performance has been observed as compared to the existing wavelet-based denoising methods with regard to quantitative and qualitative metrics.

scholarly journals Fusion of Medical Images in Wavelet Domain: A Hybrid Implementation

2020 ◽  
Vol 122 (1) ◽  
pp. 303-321
Author(s):  
Satya Prakash Yadav ◽  
Sachin Yadav
Keyword(s):  
Medical Images ◽  
Wavelet Domain
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