Liver Diseases Diagnosis Using Fuzzy Logic
DOI:
https://doi.org/10.32792/jeps.v10i1.39Keywords:
Fuzzy logic, Liver disease, Hepatitis viral, Features extractionAbstract
In this paper, a new system for liver diseases diagnosis has suggested based on using fuzzy logic byanalyzing histological liver images. The suggested system has performed in four steps: the first step is
a pre-processing step where the image has enhanced to improve its quality; the goal of image improving
is to obtain an image with a high contrast and visual details. The second step is for image analysis by
using wavelet transform to decompose and analysis the images into sub-bands. The third step is to
extract best features, which will be use the results from the wavelet transform to obtain most important
features. The fourth stage is by using the fuzzy logic system to diagnose the livers diseases types (Auto
immune, Non-autoimmune, Alcoholic and Hepatitis A, B, C, D and E). The performance of the
suggested system has tested and evaluated using 86 histological images and the experimental results
confirmed that the proposed system gave 98% accuracy.
References
. Bendi, V.R, Surendra, M. P., Venkateswarlu, N. B, “A Critical Study of Selected Classification
Algorithms for Liver Disease Diagnosis”, International Journal of Database Management Systems
(IJDMS), Vol.3, No.2, 2011, pp 102-104.
. Karthik, S., A. Priyadarishini, J. Anuradha, B. K. Tripathy, “Classification and Rule Extraction
using Rough Set for Diagnosis of Liver Disease and its Types”, Journal of Advances in Applied Science
Research, Vol. 2 No. 3, 2011.
. Ekong, V.E., 2 Onibere, E.A., 3 Imianvan, A.A "Fuzzy Cluster Means System for the Diagnosis
of Liver Diseases" IJCST Vol. 2, Issue 3, September 2011.
C. Sidney Burrus, Ramesh A. Gopinath, and Haitao Gue. “Introduction to Wavelets and Wavelet
Transforms: A primer”. Prentice Hall Inc. Upper Saddle River, New Jersy. USA. 1998.
Graps, Amara. "An introduction to wavelets." IEEE computational science and engineering 2,
no. 2 (1995): pp 50-61.
Ganic, E and Eskiciogulu, AM and others. “Robust embedding of Visual Watermarks using
DWTSVD Journal of Electronic Imaging”, 2005.
Polikar R, Keinert F, Greer M.H. (2001). Wavelet analysis of event related potentials for early
diagnosis of Alzheimer’s disease. In: A. Wavelets in Signal and Image Analysis, From Theory to
Practice, Kluwer Academic Publishers, Boston, 2001.
AlMuhit A, Islam S. and Othman M. (2004). VLSI Implementation of Discrete Wavelet
Transform (DWT) for Image Compression. 2nd International Conference on Autonomous Robots and
Agents December 13-15, 2004 Palmerston North, NewZealand
. D. Gupta and S. Choubey, “Discrete Wavelet Transform for Image Processing,” International
Journal of Emerging Technology and Advanced Engineering, vol. 4, no. 3, pp. 598-602, 2015.
. A. Susanto, D. R. I. M. Setiadi, C. A. Sari, and E. H. Rachmawanto,
“Hybrid Method using HWT-DCT for Image Watermarking,” International Conference on Information
Technology for Cyber and IT Service Management (CITSM), Denpasar, 2017.
. M. M. Sathik and S.S. Sujatha, “A Novel DWT Based Invisible Watermarking Technique for
Digital Images,” International Arab Journal of e-Technology, vol. 2, no. 3, pp. 167-173, 2012.
. P. W. Adi, F. Z. Rahmanti and N. A. Abu, “High Quality Image Steganography on Integer Haar
Wavelet Transform using Modulus Function,” in International Conference on Science in Information
Technology (ICSITech), Yogyakarta, 2015.
. Sunita P. Aware “Image Retrieval Using Co-Occurrence Matrix &Texton Co-Occurrence
Matrix for High Performance” International Journal of Advances in En-gineering & Technology, Vol.
, Issue 2, pp. 280-291. 2013.
Fritz Albregtsen, “Statistical Texture Measures Computed from Gray Level Co-ocurrence
Matrices”, Image Processing Laboratory Department of Informatics University of Oslo November 5,
R. K. Thakur and C. Saravanan,"Classification of color hazy images," in Electrical, Electronics,
and Optimization Techniques (ICEEOT), International Conference on, 2016, pp. 2159-2163.
M. M. Sathik and S.S. Sujatha, “A Novel DWT Based Invisibl Watermarking Technique for
Digital Images,” International Arab Journal of e-Technology, vol. 2, no. 3, pp. 167-173, 2012
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