%T Surface analysis of psoriasis for PASI scaliness assessment
%A H. Nugroho
%A Nazr-E-Batool
%A M.H.A. Fadzil
%A P.A. Venkatachalam
%C Kuala Lumpur
%P 798-802
%X Psoriasis is a skin disorder which typically consists of red plaques covered by silvery-white scales. The extent of the psoriasis lesion has to be assessed in determining treatment efficacy. PASI (Psoriasis Area and Severity Index) is gold standard for assessing the extent of psoriasis lesion. Scaliness is one of the parameters of PASI scoring. However, determining this parameter is found to be subjective as there are inter and intra observer variations. In this work, we develop an image processing method for PASI scaliness scoring. The method converts the depth information of the 3D lesion images (surfaces) into 2D grayscale images. Gray Level Co-occurrence Matrix (GLCM) is used to analyze the 2D images. From 14 patients with scaliness scores 1, 2 and 3, results show that the method has the potential to determine PASI scaliness score. ©2007 IEEE.
%K Cobalt; Image enhancement; Image processing; Neural networks; Parameter estimation; Two dimensional, 2d images; Depth informations; Gold standards; Grayscale images; Image processing - methods; Lesion images; Severity indices; Skin disorders, Three dimensional
%O cited By 2; Conference of 2007 International Conference on Intelligent and Advanced Systems, ICIAS 2007 ; Conference Date: 25 November 2007 Through 28 November 2007; Conference Code:74506
%L scholars190
%J 2007 International Conference on Intelligent and Advanced Systems, ICIAS 2007
%D 2007
%R 10.1109/ICIAS.2007.4658496