An Algorithm for Diagnosis of the Three
Kinds of Constitutional Jaundice

Shaker Ali, Zou Beiji, and Abbas Ali
School of Information Science and Engineering, Central South University, China

Abstract: In this paper we have made an algorithm to diagnose the Constitutional Jaundice (Dubin-Johnson, Gilbert and Rotor ‎syndrome) the algorithm is decomposed into two parts: 1) using Wavelet Transform to analyse the image; via Wavelet ‎Transform we collected three features for each kind of disease 2) calculates the percentage of the gray scales (percentage of ‎white and black colour) for each image via its histogram, it will collect two features for each kind of disease. In total there will ‎be five values; these five values will be the inputs for the fuzzy logic that will decide the kind of disease based on these values. ‎We made experiments for 55 cases mostly for children who suffered from different kinds of Constitutional Jaundice. Our ‎algorithm yields more accurate results compared to the diagnosis by a doctor’s eyes only.‎

Keywords: Medical diagnosis, Constitutional Jaundice, segmentation, Wavelet Transforms, and fuzzy logic.‎