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A smartphone application for psoriasis segmentation and classification (Conference Presentation)

Psoriasis is a chronic skin disease affecting approximately 125 million people worldwide. Currently, dermatologists monitor changes of psoriasis by clinical evaluation or by measuring psoriasis severity scores over time which lead to Subjective management of this condition. The goal of this paper is to develop a reliable assessment system to quantitatively assess the changes of erythema and intensity of scaling of psoriatic lesions. A smartphone deployable mobile application is presented that uses the smartphone camera and cloud-based image processing to analyze physiological characteristics of psoriasis lesions, identify the type and stage of the scaling and erythema. The application targets to automatically evaluate Psoriasis Area Severity Index (PASI) by measuring the severity and extent of psoriasis. The mobile application performs the following core functions: 1) it captures text information from user input to create a profile in a HIPAA compliant database. 2) It captures an image of the skin with psoriasis as well as image-related information entered by the user. 3) The application color correct the image based on environmental lighting condition using calibration process including calibration procedure by capturing Macbeth ColorChecker image. 4) The color-corrected image will be transmitted to a cloud-based engine for image processing. In cloud, first, the algorithm removes the non-skin background to ensure the psoriasis segmentation is only applied to the skin regions. Then, the psoriasis segmentation algorithm estimates the erythema and scaling boundary regions of lesion. We analyzed 10 images of psoriasis images captured by cellphone, determined PASI score for each subject during our pilot study, and correlated it with changes in severity scores given by dermatologists. The success of this work allows smartphone application for psoriasis severity assessment in a long-term treatment.