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access icon free Mesh-free approach for enhancement of mammograms

© The Institution of Engineering and Technology
Received 31/03/2017, Accepted 29/10/2017, Revised 13/10/2017, Published 30/10/2017

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.

Inspec keywords: image enhancement; medical image processing; mammography; finite difference methods; radial basis function networks

Other keywords: mesh-free radial basis function; contrast limited adaptive histogram equalisation; peak signal-to-noise ratio; image enhancement; mammograms enhancement; unsharp masking; Mini-Mammographic Image Analysis Society; mesh-based finite difference method; linear diffusion equation; image contrast; contrast enhancement technique; mesh-free approach; image processing techniques; digital database; mesh-free-based RBF collocation method

Subjects: Computer vision and image processing techniques; X-ray techniques: radiography and computed tomography (biomedical imaging/measurement); Numerical approximation and analysis; Differential equations (numerical analysis); Optical, image and video signal processing; Neural computing techniques; X-rays and particle beams (medical uses); Patient diagnostic methods and instrumentation; Differential equations (numerical analysis); Biology and medical computing

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