Open AccessMesh‐free approach for enhancement of mammograms
Author(s) -
Kashyap Kanchan Lata,
Bajpai Manish Kumar,
Khanna Pritee,
Giakos George
Publication year - 2018
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2017.0326
Subject(s) - unsharp masking , computer science , adaptive histogram equalization , mammography , artificial intelligence , histogram equalization , contrast (vision) , histogram , computer vision , algorithm , mathematics , image (mathematics) , image processing , breast cancer , medicine , cancer
Mammogram enhancement is a key step to detect breast cancer using digital mammogram. The present study investigates mesh‐free radial basis function (RBF) collocation method to solve linear diffusion equation for image enhancement of mammograms. The proposed algorithm is compared with the mesh‐based finite difference method as well as other existing enhancement methods such as unsharp masking, histogram equalisation, and contrast limited adaptive histogram equalisation. Specifically, figure‐of‐merits with emphasis on image contrast and computational time are assessed and compared with different image processing techniques. The proposed algorithm has been applied towards the enhancement of all 322 sample mammogram images of Mini‐Mammographic Image Analysis Society and randomly selected 300 sample images from Digital Database for Screening Mammography databases. Finally, mean and standard deviation of contrast improvement index and peak signal‐to‐noise ratio have been estimated and presented. The outcome of this study indicates that the mesh‐free‐based RBF collocation method proves to be a computationally efficient and valuable contrast enhancement technique in an area of mammography.