Diagnosis Of Liver Disease Using Gaussian Blur Algorithm

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

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.

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

Unique Identification Number - IJEDR1502172
Page Number(s) - 995-1007
Pubished in - Volume 3 | Issue 2 | May 2015
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)

  Devishree.V,  Anjali Nair,  Bhavya S.N,,  Thanuja.E,   "Diagnosis Of Liver Disease Using Gaussian Blur Algorithm", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.3, Issue 2, pp.995-1007, May 2015, Available at :http://www.ijedr.org/papers/IJEDR1502172.pdf