A Novel Pre-Processing Approach for the Denoising of Alzheimer Disease Image Dataset

Authors

  • M. Natarajan Assistant Professor, Division of Computer and Information Science, Annamalai University, Annamalai Nagar, Tamil Nadu, India
  • S. Sathiamoorthy Assistant Professor, Division of Computer and Information Science, Annamalai University, Annamalai Nagar, Tamil Nadu, India

DOI:

https://doi.org/10.51983/ajcst-2018.7.2.1870

Keywords:

Thresholding, Histogram Equalization, Wavelet transform, Denoising

Abstract

Medical imaging doing an indispensable part in the area of medicine. Noise in the image is maddening as it worsens the quality of image. Thus, removal of noise is perpetually a problematic work in the images of all domain. Alzheimer’s disease, a neurological dysfunction in which destruction of cells in brain creates mental weakening and memory loss. The distinguished reason for Alzheimer’s disease is low brain activity and low blood flow. We proposed a framework for removal of noise in Alzheimer disease image using histogram equalization, thresholding, open morphological operation and a wavelet transform. This framework reduces the noise and significantly better than the existing methods used for Alzheimer disease images.

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Published

18-08-2021

How to Cite

Natarajan, M., & Sathiamoorthy, S. (2021). A Novel Pre-Processing Approach for the Denoising of Alzheimer Disease Image Dataset. Asian Journal of Computer Science and Technology, 7(2), 107–112. https://doi.org/10.51983/ajcst-2018.7.2.1870