DocumentCode :
1838716
Title :
Area Assessment of Psoriasis Lesion for PASI Scoring
Author :
Ihtatho, D. ; Fadzil, M.H.A. ; Affandi, A.M. ; Hussein, S.H.
Author_Institution :
Univ. Teknol. PETRONAS, Tronoh
fYear :
2007
fDate :
22-26 Aug. 2007
Firstpage :
3446
Lastpage :
3449
Abstract :
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.
Keywords :
biomedical optical imaging; computer vision; diseases; image colour analysis; medical image processing; skin; CIE L*a*b* colour space; Euclidean distance; PASI scoring; computer vision method; disease control; erythema; ethnic origins; genetic fault; hue-chroma space; plaque scaliness; psoriasis area-and-severity index; psoriasis lesion; skin disorder; skin tones; Area measurement; Current measurement; Diseases; Euclidean distance; Genetics; Gold; Lesions; Measurement standards; Skin; Thickness measurement; 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;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE
Conference_Location :
Lyon
ISSN :
1557-170X
Print_ISBN :
978-1-4244-0787-3
Type :
conf
DOI :
10.1109/IEMBS.2007.4353072
Filename :
4353072
Link To Document :
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