@ARTICLE{ iet:/content/journals/10.1049/iet-ipr.2017.0326, author = {Kanchan Lata Kashyap}, author = {Manish Kumar Bajpai}, author = {Pritee Khanna}, author = {George Giakos}, keywords = {image contrast;linear diffusion equation;mesh-based finite difference method;mammograms enhancement;peak signal-to-noise ratio;image enhancement;digital database;mesh-free-based RBF collocation method;contrast enhancement technique;unsharp masking;mesh-free radial basis function;contrast limited adaptive histogram equalisation;image processing techniques;mesh-free approach;Mini-Mammographic Image Analysis Society;}, ISSN = {1751-9659}, language = {English}, abstract = {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.}, title = {Mesh-free approach for enhancement of mammograms}, journal = {IET Image Processing}, issue = {3}, volume = {12}, year = {2018}, month = {March}, pages = {299-306(7)}, publisher ={Institution of Engineering and Technology}, copyright = {© The Institution of Engineering and Technology}, url = {https://digital-library.theiet.org/;jsessionid=2lan5dd37i4gn.x-iet-live-01content/journals/10.1049/iet-ipr.2017.0326} }