Overfitting control for surface reconstruction
SGP '06 Proceedings of the fourth Eurographics symposium on Geometry processing
Advances in Fuzzy Clustering and its Applications
Advances in Fuzzy Clustering and its Applications
Computational Surface and Roundness Metrology
Computational Surface and Roundness Metrology
High order polynomial surface fitting for measuring roughness of psoriasis lesion
IVIC'11 Proceedings of the Second international conference on Visual informatics: sustaining research and innovations - Volume Part I
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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 coefficients0.84 (almost perfect agreement).