@CONFERENCE\{IMM2004-03582,
    author       = "D. D. G\'{o}mez and B. K. Ersb{\o}ll and J. M. Carstensen",
    title        = "Automatic scoring of the severity of psoriasis scaling",
    year         = "2004",
    month        = "sep",
    keywords     = "psoriasis, exploratory data analysis, segmentation, decision trees, classification",
    pages        = "204-209",
    booktitle    = "Irish Machine Vision and Image Processing Conference 2004",
    volume       = "",
    series       = "",
    editor       = "",
    publisher    = "",
    organization = "",
    address      = "",
    url          = "http://www2.compute.dtu.dk/pubdb/pubs/3582-full.html",
    abstract     = "In this work, a combined statistical and image analysis method to automatically evaluate the severity of scaling in psoriasis lesions is proposed. The method separates the different regions of the disease in the image and scores the degree of scaling based on the properties of these areas. The proposed method provides a solution to the lack of suitable methods to assess the lesion and to evaluate changes during the treatment. An experiment over a collection of psoriasis images is conducted to test the performance of the method. Results show that the obtained scores are highly correlated with scores made by doctors. This and the fact that the obtained measures are continuous indicate the proposed method is a suitable tool to evaluate the lesion and to track the evolution of dermatological diseases."
}