AUTOMATED SCORING FOR SCALINESS OF PSORIASIS LESIONS USING CLUSTER SEGMENTATION

Psoriasis is a chronic skin disease and is a genetically determined inflammatory and
proliferate disease, measure by three different parameter; Redness, Scaling and
Thickness. Psoriasis is categorized as localized or generalized, based on the severity
of the disease and its overall impact on the patient's quality of life and well-being.
The most widely method used in clinical trials to evaluate psoriasis disease severity is
Psoriasis Area and Severity Index (PASI).
The objective of this project is to generate a quantitative score of scaliness for
psoriasis disease which to be used in PASI score calculation. The current PASI
scoring system is complicated to be used for scaling evaluation. Moreover, psoriasis
lesions are quite visible and therefore relatively hard to quantify with human vision.
The images used for the analysis are obtained from the dermatologist and psoriasis
website, also from General Hospital Ipoh. Throughout this project, MATLAB 7
software is used in obtaining the results. The algorithm is developed together with a
sub-system for image acquisition and processing, segmentation, texture analysis for
scaliness scores and PASI scoring based on the scales.