A quantitative technique for assessing the change in severity over time in psoriatic lesions using computer aided image analysis
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Psoriasis is a chronic skin disease affecting an estimated 125 million people worldwide. One of the key problems in the management of this condition is the objective measurement of lesion severity over time. Currently, severity is scored by clinicians using visual protocols leading to intra and inter observer variability that makes measurement of treatment efficacy subjective. In this paper, an automatic computer aided image analysis system is proposed that quantitatively assess the changes of erythema and scaling severity of psoriatic lesions in long-term treatment. The algorithm proposed in this paper works on 2D digital images by selecting features that can be used to accurately segment erythema and scaling in psoriasis lesions and assess their changes in severity, according to the popular psoriasis area and severity index (PASI). The algorithms are validated by developing linear models that correlate well with changes in severity scores given by dermatologists. To the best of our knowledge, no such computer assisted method for psoriasis severity assessment in a long-term treatment exists.
[1] Juan Lu,et al. Erythema detection in digital skin images , 2010, 2010 IEEE International Conference on Image Processing.
[2] L. Naldi,et al. The clinical spectrum of psoriasis. , 2007, Clinics in dermatology.
[3] Juan Lu,et al. Automatic Segmentation of Scaling in 2-D Psoriasis Skin Images , 2013, IEEE Transactions on Medical Imaging.
[4] Constantine Butakoff,et al. Automatic change detection and quantification of dermatological diseases with an application to psoriasis images , 2007, Pattern Recognit. Lett..