Paper Title

Diagnosis Of Liver Disease Using Gaussian Blur Algorithm

Authors

  • Devishree.V
  • Anjali Nair
  • Bhavya S.N,
  • Thanuja.E

Keywords

Classification, first-order statistics, Magnetic Resonance Imaging (MRI), region of interest, Gaussian Blur, Morphological Application. better understand the differences of the diseases and the image modalities used in this research, some of the 142 test images are described in this research work. The 142 test images used in this study were pre-diagnosed by a senior specialist at collaborating hospital, Hospital Selayang, Malaysia. healthy liver healthy liver

Abstract

In this paper, the classification of liver diseases using first-order statistics (FOS) is implemented for automatic preliminary diagnosis of liver diseases. Region of interest (ROI) extracted from MRI images are used as the input to characterize different tissue, namely liver cyst, fatty liver and healthy liver using first-order statistics. The results for first-order statistics are given. The measurements extracted from First-order statistic include entropy and correlation achieved obvious classification range in detecting different tissues in this work.

Article Type

Published

How To Cite

Devishree.V, Anjali Nair, Bhavya S.N,, Thanuja.E. "Diagnosis Of Liver Disease Using Gaussian Blur Algorithm".INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH ISSN:2321-9939, Vol.3, Issue 2, pp.995-1007, URL :https://rjwave.org/ijedr/papers/IJEDR1502172.pdf

Issue

Volume 3 Issue 2 

Pages. 995-1007

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