@article{scholars3374,
         journal = {Computers in Biology and Medicine},
           pages = {1987--2000},
            year = {2013},
           title = {3D surface roughness measurement for scaliness scoring of psoriasis lesions},
          number = {11},
            note = {cited By 13},
          volume = {43},
             doi = {10.1016/j.compbiomed.2013.08.009},
        abstract = {Psoriasis is an incurable skin disorder affecting 2-3 of the world population. The scaliness of psoriasis is a key assessment parameter of the Psoriasis Area and Severity Index (PASI). Dermatologists typically use visual and tactile senses in PASI scaliness assessment. However, the assessment can be subjective resulting in inter- and intra-rater variability in the scores. This paper proposes an assessment method that incorporates 3D surface roughness with standard clustering techniques to objectively determine the PASI scaliness score for psoriasis lesions. A surface roughness algorithm using structured light projection has been applied to 1999 3D psoriasis lesion surfaces. The algorithm has been validated with an accuracy of 94.12. Clustering algorithms were used to classify the surface roughness measured using the proposed assessment method for PASI scaliness scoring. The reliability of the developed PASI scaliness algorithm was high with kappa coefficients{\ensuremath{>}}0.84 (almost perfect agreement). {\^A}{\copyright} 2013 Elsevier Ltd.},
        keywords = {3D surface roughness; Clustering techniques; Fuzzy C means clustering; K-means clustering; Kappa coefficient; Polynomial surface fitting; Skin surface roughness; Structured light projection, Clustering algorithms; Skin; Surface roughness, Dermatology, accuracy; algorithm; article; Fourier transformation; human; illumination; image analysis; priority journal; psoriasis; Psoriasis Area and Severity Index; reliability; remote sensing; scar formation; skin scar; skin surface; skinfold thickness; three dimensional imaging, Agreement analysis; Fuzzy c-means clustering; k-means clustering; Polynomial surface fitting; Skin surface roughness, Algorithms; Cluster Analysis; Fuzzy Logic; Humans; Image Processing, Computer-Assisted; Psoriasis; Reproducibility of Results; Skin; Surface Properties},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84887178188&doi=10.1016\%2fj.compbiomed.2013.08.009&partnerID=40&md5=8f265f294c5693bfb42804ebd6c5e163},
            issn = {00104825},
          author = {Ahmad Fadzil, M. H. and Prakasa, E. and Asirvadam, V. S. and Nugroho, H. and Affandi, A. M. and Hussein, S. H.}
}