The Effect of Regularization Parameter within Non-blind Restoration Algorithm Using Modified Iterative Wiener Filter for Medical Image

2018 ◽  
Author(s):  
Alaa H. Sheer ◽  
Ayad A. Al-Ani
Keyword(s):  
Medical Image ◽  
Regularization Parameter ◽  
Wiener Filter ◽  
Restoration Algorithm ◽  
Blind Restoration

Research on Realization of Medical Image Restoration Based on Blind Equalization Algorithm

2020 ◽  
Vol 10 (4) ◽  
pp. 809-813
Author(s):  
Ting Han ◽  
Ruo-Han Zhao ◽  
Mo Dong
Keyword(s):  
Image Restoration ◽  
Medical Image ◽  
Medical Images ◽  
Blind Equalization ◽  
Diagnostic Errors ◽  
Degradation Process ◽  
Restoration Algorithm ◽  
Equalization Algorithm ◽  
Improvement Effect ◽  
Blind Restoration

In order to study the realization of medical image restoration, this study mainly adopts blind equalization algorithm to analyze medical images, and observes the improvement effect of blind equalization technology on medical images. In the process of medical image formation, it is unavoidable to be affected by point spread function, which leads to image degradation and brings great difficulties to diagnosis, and the results of degradation are often unpredictable. The results show that the blind restoration algorithm can restore the image when the degradation process of the medical image is uncertain, which makes the medical image clearer and more accurate, brings great convenience to the diagnosis, and also reduces the diagnostic errors caused by the unclear image.

scholarly journals Mammogram image with Wiener filter and CLAHE

2017 ◽  
Vol 9 (2) ◽  
Author(s):  
Thekra Abbas ◽  
M .Nafea Jafaar
Keyword(s):  
Breast Cancer ◽  
Early Detection ◽  
Medical Diagnosis ◽  
Medical Image ◽  
Wiener Filter ◽  
Pectoral Muscle ◽  
Automated Detection ◽  
High Quality ◽  
Mammogram Image

      Many of the women in worlds die because of breast cancer and early detection will save the lives of many women. A mammogram is a special medical image in the breast. The mammogram image contains artifacts and wedge.     In this paper the mammogram image enhances by applied the Wiener filter to remove noise and apply Contrast Limited Adaptive Histogram Equitation (CLAHE) to improve a quality of mammogram image. Before applying them made number step to remove artifacts and wedge, background and pectoral muscle these know. The result indicted obtain mammogram image only breast profile, with a nice smooth, safe edge, and high quality.        These results prove that effective and convenient assistance for medical diagnosis. Hence, the proposed method definitely can be considered for automated detection of abnormality like benign, malignant and micro calcifications.

scholarly journals Echocardiography image denoising using fractal wavelet transform

2018 ◽  
Vol 5 ◽  
pp. 23-33
Author(s):  
Reena Manandhar ◽  
Sanjeeb Prashad Pandey
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Gaussian Noise ◽  
Medical Image ◽  
Signal To Noise Ratio ◽  
Wiener Filter ◽  
Hard Thresholding ◽  
Echocardiography Image ◽  
Different Types

One of the most important areas in image processing is medical image processing where the quality of the images has become an important issue. Most of the medical images are corrupted with the visual noise, and one of the such images is echocardiography image where this effect is more. So, this research aims to denoise the echocardiography image with fractal wavelet transform and to compare its performance with other wavelet based algorithm like hard thresholding, soft thresholding and wiener filter. Initially, the image is corrupted by the Gaussian noise with varying noise variances and is denoised using above mentioned different wavelet based denoising techniques. On comparison of the obtained results, it is observed that the fractal wavelet transform is well suited for highly degraded echocardiography images in terms of Mean Square Error (MSE) and Peak Signal To Noise Ratio (PSNR) than other wavelet based denoising methods. Further, the work could be enhanced to denoise the echocardiography image corrupted by other different types of noise. This research is limited to denoise the echocardiography image corrupted with Gaussian noise only.

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