Experiments on the Interpolation of the Histogramed MR Brain Images for Resolution Enhancement

Magnetic resonance imaging (MRI) is an incredible testing method which provides appropriate
anatomical images of the body. For the diagnosis, high resolution MR images are essential to extract
the detailed information about the diseases. However, with the measured MR images it’s a
challenging issue in extracting the detailed information associated to disease for the posterior analysis
or treatment. Usually to improve the resolution of the MR image, histogram equalization process has
to be applied. In this paper, interpolation method is applied to improve the resolution of MR brain
images for the histogram-ed images. And for the assessment of the skillfulness of introduced method,
performance metrics such as peak signal to noise ratio (PSNR) and absolute mean brightness error
(AMBE) are measured. The peak of signal for the enhanced images through interpolation will be much
better and may have the good variation to the mean brightness error. With this there can be potential
to the artificial intelligence for better diagnosis in complex decisive instances.