Title :
In vivo 3D thickness measurement of skin lesion
Author :
Hani, A.F.M. ; Fitriyah, Hurriyatul ; Prakasa, Esa ; Asirvadam, V.S. ; Hussein, S.H. ; Azura, M.A.
Author_Institution :
Electr. & Electron. Eng. Dept., Univ. Teknol. PETRONAS, Tronoh, Malaysia
fDate :
Nov. 30 2010-Dec. 2 2010
Abstract :
Thickness is one of the morphological characteristic of skin lesion that represents severity condition. Dermatologists use tactile inspection to subjectively assess the thickness by feeling the alteration of the lesion from its surrounding normal skin. In this paper, a method to objectively measure the abnormal elevation occurs in skin lesions is presented. A 3D fringe projection scanner is used to obtain 3D surface profile of the lesion. Thickness of a lesion is defined as the elevations of lesion surface from its lesion base. The lesion base is determined from the neighboring normal skin using a 3D surface interpolation technique. The lesion elevations are determined in a 3D space grid by subtracting the elevation of the lesion surface profile from the interpolated lesion base profile at all corresponding locations thus giving lesion thickness as the average value of the elevations. The algorithm has been validated using 3D surface samples with an error of 0.031 mm ± SD 0.014 mm (95% Confidence Interval: ±0.0011 mm). The validated algorithm has been successfully applied to measure thicknesses of 450 psoriasis plaque lesions with severity level ranging from mild to severe and thickness ranging from 0.021 mm to 0.883 mm. From the measured thicknesses, Psoriasis Area and Severity Index (PASI) thickness scores 0 to 4 are then determined using unsupervised K-means Clustering.
Keywords :
biomedical measurement; cancer; interpolation; medical diagnostic computing; skin; thickness measurement; unsupervised learning; 3D fringe projection scanner; 3D surface interpolation; 3D surface profile; Psoriasis Area and Severity Index; dermatologists; in vivo 3D thickness measurement; psoriasis plaque; skin lesion; tactile inspection; unsupervised K-means clustering; Head; Image segmentation; Lesions; Surface treatment; Thickness measurement; Three dimensional displays; Ultrasonic variables measurement; PASI; in vivo 3D measurement; lesion thickness; skin lesion;
Conference_Titel :
Biomedical Engineering and Sciences (IECBES), 2010 IEEE EMBS Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4244-7599-5
DOI :
10.1109/IECBES.2010.5742219