Validation on 3D surface roughness algorithm for measuring roughness of psoriasis lesion

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 meth...

Full description

Bibliographic Details
Main Authors: Ahmad Fadzil, M Hani, Prakasa, Esa, Nugroho, Hermawan, Affandi, Azura Mohd, Hussein, Suraiya Hussein
Format: Citation Index Journal
Published: World Academy of Science Engineering and Technology 2010
Subjects:
Online Access:http://scholars.utp.edu.my/id/eprint/3184/
_version_ 1848659363927949312
author Ahmad Fadzil, M Hani
Prakasa, Esa
Nugroho, Hermawan
Affandi, Azura Mohd
Hussein, Suraiya Hussein
author_facet Ahmad Fadzil, M Hani
Prakasa, Esa
Nugroho, Hermawan
Affandi, Azura Mohd
Hussein, Suraiya Hussein
author_sort Ahmad Fadzil, M Hani
building UTP Institutional Repository
collection Online Access
description 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 modeled by a rough surface. The rough surface is created by superimposing a smooth base (curve) surface with a triangular waveform. For roughness determination, a polynomial surface fitting is used to estimate base surface followed by a subtraction between rough and base surface to give height map matrix (surface deviations). Roughness index is calculated by using average roughness equation to the height map matrix. The roughness algorithm has been tested to 55 lesion models. From roughness validation result, only 2 models can not be accepted (percentage error is greater than 10%). These errors occur due the tapes not mounted to the curve surface properly. This has resulted in folding at the edges. 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 Ra is -0.9488, its shows there is a strong relation between G and Ra. The algorithm needs to be improved by surface filtering, especially to overcome a problem with noisy data.
first_indexed 2025-11-13T07:29:15Z
format Citation Index Journal
id oai:scholars.utp.edu.my:3184
institution Universiti Teknologi Petronas
institution_category Local University
last_indexed 2025-11-13T07:29:15Z
publishDate 2010
publisher World Academy of Science Engineering and Technology
recordtype eprints
repository_type Digital Repository
spelling oai:scholars.utp.edu.my:31842014-04-01T03:04:02Z http://scholars.utp.edu.my/id/eprint/3184/ Validation on 3D surface roughness algorithm for measuring roughness of psoriasis lesion Ahmad Fadzil, M Hani Prakasa, Esa Nugroho, Hermawan Affandi, Azura Mohd Hussein, Suraiya Hussein QA75 Electronic computers. Computer science RL Dermatology 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 modeled by a rough surface. The rough surface is created by superimposing a smooth base (curve) surface with a triangular waveform. For roughness determination, a polynomial surface fitting is used to estimate base surface followed by a subtraction between rough and base surface to give height map matrix (surface deviations). Roughness index is calculated by using average roughness equation to the height map matrix. The roughness algorithm has been tested to 55 lesion models. From roughness validation result, only 2 models can not be accepted (percentage error is greater than 10%). These errors occur due the tapes not mounted to the curve surface properly. This has resulted in folding at the edges. 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 Ra is -0.9488, its shows there is a strong relation between G and Ra. The algorithm needs to be improved by surface filtering, especially to overcome a problem with noisy data. World Academy of Science Engineering and Technology 2010-03 Citation Index Journal PeerReviewed Ahmad Fadzil, M Hani and Prakasa, Esa and Nugroho, Hermawan and Affandi, Azura Mohd and Hussein, Suraiya Hussein (2010) Validation on 3D surface roughness algorithm for measuring roughness of psoriasis lesion. [Citation Index Journal]
spellingShingle QA75 Electronic computers. Computer science
RL Dermatology
Ahmad Fadzil, M Hani
Prakasa, Esa
Nugroho, Hermawan
Affandi, Azura Mohd
Hussein, Suraiya Hussein
Validation on 3D surface roughness algorithm for measuring roughness of psoriasis lesion
title Validation on 3D surface roughness algorithm for measuring roughness of psoriasis lesion
title_full Validation on 3D surface roughness algorithm for measuring roughness of psoriasis lesion
title_fullStr Validation on 3D surface roughness algorithm for measuring roughness of psoriasis lesion
title_full_unstemmed Validation on 3D surface roughness algorithm for measuring roughness of psoriasis lesion
title_short Validation on 3D surface roughness algorithm for measuring roughness of psoriasis lesion
title_sort validation on 3d surface roughness algorithm for measuring roughness of psoriasis lesion
topic QA75 Electronic computers. Computer science
RL Dermatology
url http://scholars.utp.edu.my/id/eprint/3184/