Abstract
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. We develop a method to segment psoriasis lesion in the early stage of diagnosis. In this stage region of interest is very clear that help the k-means clustering to achieve accuracy segmentation. This method has produced a mask which includes the region of interest as white color and background as black color. In the second diagnosis level (scan the region of interest), if the patient case has enhanced, the region of interest will disappear and that will affect the segmentation method and make it a difficult challenge. To avoid this problem we have used the mask of the early stage scans and applied on the second scan image to see the difference between the two regions scan. This process helps us to evaluate severity changes the patient case enhancement on erythema and scaling of lesions. 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 objectives 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. Monitoring severity change psoriasis lesion measures are highly correlated with the dermatologist’s decisions than PASI. This and the fact that the obtained measures are continuous indicate the proposed methods are a suitable tool to evaluate the lesion and to track the evolution of dermatological diseases. These systems were evaluated by a number of dermatologists with different experiences.
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