AUTOMATED SCORING FOR SCALINESS OF PSORIASIS LESIONS USING EDGE DETECTION

Skin diseases affect 20-30% of the population at any one time, interfering with
activities in 10%. Psoriasis, an Mamniatory skin condition and currently incurable is
one of the most common skin diseases. About 80% of people who develop psoriasis
have plaque psoriasis, which appears as patches of raised, reddish skiii covered by
silvery-white scale. The Psoriasis Area and Severity Index (PASI) is the most widely
Used tool to assess psoriasis disease severity in clinical trials, although it can be
exceedingly cumbersome for use in daily clinical practice. It is proven to be
extremely effective in assessing Psoriasis. When Using the PASI, psoriatic plaques are
graded based on three criteria: redness, thickness, and scaliness. For the time being,
the PASI-scoring are subjective since the assessments are done Visually by the
dermatologist. The assessment will result in inter-individual variation between
estimates due to different level of experiences and visual acuity.
The aim of this project is to develop an automated scoring for scaliness of Psoriasis
lesions program Using MATLAB. This project will be Using 2-D Psoriasis images
obtained from General Hospital, Kuala Lumpur and medical database online. The
MATLAB software will be Used to develop algorithms that are capable to read
images of Psoriasis and grade the scaliness scores using the PASI-score texture
analysis. The targeted system will include subsystem for acquiring the images, image
processing, segmentation, texture analysis for scaliness score and severity based on
PASI system.