AN IMAGE BASED SYSTEM TO OBJECTIVELY SCORE THE DEGREE OF SCALING IN PSORIASIS LESIONS

Skin diseases affect 20-30% of the population at any one time, seriously interfering
with activities in 10%. Psoriasis is one of the most common skin diseases; it is non
infectious, inflammatory disease of the skin. It is characterised by erythematous
plaques with adherent silvery scales. There are known inherited genetic factors and
several documented environmental factors that affect the clinical course of psoriasis.
Men and women are equally affected and often seen between 15 to 15 years [l].The
treatment of psoriasis requires the doctor to monitor the severity for each individual.
They need to knowthe patient's condition either fully heals, moderate or bad.
A standard parameter for measuring the severity and coverage of psoriasis is used;
namely Psoriasis Area and Severity Index (PASI). The PASI has been used for more
than ten years and it is widely use aroundthe world in the management of psoriasis. It
is proved to be extremely effective in accessing psoriasis .Whilst it is not perfect, but it
is the best method of assessment of psoriasis currently available [2]. This PASI have
measure four variables which are the surface area of the psoriasis, the severity of
Erythma(redness), the amount of scaling and the thickness of the plague. The surface
area will be scored from 0 to 6 while the others will be scored from 0 to 4 depending
on how much the percentage of psoriasis coverage and how severe the psoriasis is.
Several problem are identified in current assessment of PASI, such problem are
parameters measured are inaccurate, patient have to wait longer time for the result of
further treatment and the evaluation in general performed on the base of clinical
experience only.
This project report focuses on the assessment of scaliness using a computerized
system for use in PASI calculation -The system used is image processing toolbox that
available in MATLAB 7.0. The designed system will help dermatologist to objectively
score the degree of scaling in psoriasis lesions. The project requires the author to
import the digital image of infected skin, analyze the image in MATLAB 7.0, and
provide an accurate score for PASFs scaling parameter. The methods used are the
grayscale conversion, edge detection technique, image segmentation and pixels
percentage calculation. The final results are the individual PASI score together with
his personal data display on graphical user interface (GUI).