Area assessment of psoriasis lesion for PASI scoring.

D., Ihtatho and M.H. A., Fadzil and A.M., Affandi and S.H., Hussein (2007) Area assessment of psoriasis lesion for PASI scoring. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, 2007. pp. 3446-3449. ISSN 1557170X

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Psoriasis is a skin disorder which is caused by genetic fault. There is no cure for psoriasis, however, there are many treatment modalities to help control the disease. To evaluate treatment efficacy, PASI (Psoriasis Area and Severity Index) which is the current gold standard method is used to measure psoriasis severity by evaluating the area, erythema, scaliness and thickness of the plaques. However, the calculation of PASI can be tedious and subjective. In this work, we develop a computer vision method that determines one of the PASI parameter, the lesion area. The method isolates healthy (or healed) skin areas from lesion areas by analyzing the hue and chroma information in the CIE L*a*b* colour space. Centroids of healthy skin and psoriasis in the hue-chroma space are determined from selected sample. Euclidean distance of all pixels from each centroid is calculated. Each pixel is assigned to the class with minimum Euclidean distance. The study involves patients from three different ethnic origins having different skin tones. Results obtained show that the proposed method is comparable to the dermatologist visual approach.

Item Type: Article
Uncontrolled Keywords: adult; algorithm; article; artificial intelligence; automated pattern recognition; classification; colorimetry; comparative study; computer assisted diagnosis; epiluminescence microscopy; evaluation; female; hospitalization; human; image enhancement; male; methodology; psoriasis; reproducibility; sensitivity and specificity; Adult; Algorithms; Artificial Intelligence; Colorimetry; Dermoscopy; Female; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Male; Pattern Recognition, Automated; Psoriasis; Reproducibility of Results; Sensitivity and Specificity; Severity of Illness Index
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Departments / MOR / COE: Departments > Electrical & Electronic Engineering
Depositing User: Prof Ir Dr Ahmad Fadzil Mohd Hani
Date Deposited: 09 Mar 2010 02:01
Last Modified: 19 Jan 2017 08:27

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