eprintid: 1284
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/12/84
datestamp: 2023-11-09 15:49:26
lastmod: 2023-11-09 15:49:26
status_changed: 2023-11-09 15:39:24
type: article
metadata_visibility: show
creators_name: Fadzil Ahmad, M.H.
creators_name: Prakasa, E.
creators_name: Fitriyah, H.
creators_name: Nugroho, H.
creators_name: Affandi, A.M.
creators_name: Hussein, S.H.
title: Validation on 3D surface roughness algorithm for measuring roughness of psoriasis lesion
ispublished: pub
keywords: 3D surface roughness; Digital image analysis; Direct contact; Flat surfaces; Gold standards; Height map; matrix; Noisy data; Pearson's correlation coefficients; Percentage error; Polynomial surface fitting; Red lesions; Rough surfaces; Roughness index; Scanned images; Severity index; Skin disease; Surface filtering; Tactile sense; Triangular waveform; Validation results, Abrasives; Algorithms; Fiber optic sensors; Image analysis; Image quality; Polynomials; Skin; Surface measurement; Surface properties; Surface roughness, Dermatology
note: cited By 7
abstract: Psoriasis is a widespread skin disease affecting up to 2 population with plaque psoriasis accounting to about 80. It can be identified as a red lesion and for the higher severity the lesion is usually covered with rough scale. Psoriasis Area Severity Index (PASI) scoring is the gold standard method for measuring psoriasis severity. Scaliness is one of PASI parameter that needs to be quantified in PASI scoring. Surface roughness of lesion can be used as a scaliness feature, since existing scale on lesion surface makes the lesion rougher. The dermatologist usually assesses the severity through their tactile sense, therefore direct contact between doctor and patient is required. The problem is the doctor may not assess the lesion objectively. In this paper, a digital image analysis technique is developed to objectively determine the scaliness of the psoriasis lesion and provide the PASI scaliness score. Psoriasis lesion is modelled by a rough surface. The rough surface is created by superimposing a smooth average (curve) surface with a triangular waveform. For roughness determination, a polynomial surface fitting is used to estimate average surface followed by a subtraction between rough and average surface to give elevation surface (surface deviations). Roughness index is calculated by using average roughness equation to the height map matrix. The roughness algorithm has been tested to 444 lesion models. From roughness validation result, only 6 models can not be accepted (percentage error is greater than 10). These errors occur due the scanned image quality. Roughness algorithm is validated for roughness measurement on abrasive papers at flat surface. The Pearson's correlation coefficient of grade value (G) of abrasive paper and R a is -0.9488, its shows there is a strong relation between G and R a. The algorithm needs to be improved by surface filtering, especially to overcome a problem with noisy data.
date: 2010
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-78651575653&partnerID=40&md5=a9505f462750ea97532654bb77b55c25
full_text_status: none
publication: World Academy of Science, Engineering and Technology
volume: 63
pagerange: 116-121
refereed: TRUE
issn: 2010376X
citation:   Fadzil Ahmad, M.H. and Prakasa, E. and Fitriyah, H. and Nugroho, H. and Affandi, A.M. and Hussein, S.H.  (2010) Validation on 3D surface roughness algorithm for measuring roughness of psoriasis lesion.  World Academy of Science, Engineering and Technology, 63.  pp. 116-121.  ISSN 2010376X