Liver Diseases Diagnosis Using Fuzzy Logic


  • Shaker K. Ali Computer Department, Computer Sciences and Mathematics College, University of Thi-Qar, Thi-Qar, Iraq.
  • Etab M. Attia Computer Department, College of Education for Pure Science, University of Thi-Qar, Thi-Qar, Iraq


Fuzzy logic, Liver disease, Hepatitis viral, Features extraction


In this paper, a new system for liver diseases diagnosis has suggested based on using fuzzy logic by
analyzing 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.


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