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August 2019 Vol.5 No.1

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Chehelamirani M

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Merit Research Journal of Engineering, Pure and Applied Sciences  (ISSN: 2408-7033) Vol. 5(1) pp. 014-018, August, 2019

Copyright © 2019 Merit Research Journals

DOI: 10.5281/zenodo.3374916

Original Research Article

Using Adaptive Median Filter for Noise Removal from Image to Diagnose Breast Cancer

 
 
 

Abdollah Jafari Chashmi1* and Mehdi Chehelamirani2

 

1Urmia University Urmia, Iran
2Associate Professor, Urmia University, Urmia, Iran

*Corresponding Author’s E-mail: abdolahjafari90@gmail.com

Accepted June 12, 2019

 

Abstract

 

Breast cancer is one of the main causes of fatality among women around the world. Mammography is a basic screening technique in fast diagnosis of tumor in the breast. The main goal of mammography is to recognize small masses/tumors in the shortest time, since these masses can be the sign of cancer. But due to existence of noise, low and opaque contrast and fuzziness of mammograms’ images, diagnosis of small masses is difficult. Hence, the images of mammograms shall be improved. Recovering the images is carried out for better display of mammographic special features including mass and micro classification, and exaggeration of certain properties is done for simple and fast diagnosis. “Makendor” and “Helali” reviewed different techniques of removing noise and image enhancement in order to determine the enhancement technique appropriate to mammogram’s images. Mammograms remove the noise by linear and non-linear filtering techniques. The operations of these techniques are measured by using Root Mean Square Error (RMSE) and Peak Signal Noise Rate (PSNR). Finally, the contrast of images is improved by histogram techniques.

Keywords: Breast cancer, Mammography, Noise removal, Root Mean Square Error (RMSE), Peak Signal Noise Rate (PSNR), Contrast Limited Adaptive Histogram Equivalent (CLAHE)















 































 

 

 

















 
 


 






 




 
 









 








 
























 

 
 
   
   
   
   
   
   
   
   
   
   
   
 
 
 
 
 
 
 
 
   
 
                         

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