Vitiligo is an acquired pigmentary skin disorder characterized by depigmented macules
that result from damage to and destruction of epidermal melanocytes. Visually, the
vitiligous areas are paler in contrast to normal skin or completely white due to the lack of
pigment melanin. The course of vitiligo is unpredictable where the vitiligous skin lesions
may remain stable for years before worsening.
Vitiligo treatments have two objectives, to arrest disease progression and to re-pigment
the vitiligous skin lesions. To monitor the efficacy of the treatment, dermatologists
observe the disease directly, or indirectly using digital photos. Currently there is no
objective method to determine the efficacy of the vitiligo treatment. Physician's Global
Assessment (PGA) scale is the current scoring system used by dermatologists to evaluate
the treatment. The scale is based on the degree of repigmentation within lesions over
time. This quantitative tool however may not be help to detect slight changes due to
treatment as it would still be largely dependent on the human eye and judgment to
produce the scorings. In addition, PGA score is also subjective, as it varies with
dermatologists.
The progression of vitiligo treatment can be very slow and can take more than 6 months.
It is observed that dermatologists find it visually hard to determine the areas of skin
repigmentation due to this slow progress and as a result the observations are made after a
longer time frame. The objective of this research is to develop a tool that enables
dermatologists to determine and quantify areas of repigmentation objectively over a
shorter time frame during treatment. The approaches towards achieving this objective are
based on digital image processing techniques.
Skin color is due to the combination of skin histological parameters, namely pigment
melanin and haemoglobin. However in digital imaging, color is produced by combining three different spectral bands, namely red, green, and blue (RGB). It is believed that the
spatial distribution of melanin and haemoglobin in skin image could be separated.
It is found that skin color distribution lies on a two-dimensional melanin-haemoglobin
color subspace. In order to determine repigmentation (due to pigment melanin) it is
necessary to perform a conversion from RGB skin image to this two-dimensional color
subspace. Using principal component analysis (PCA) as a dimensional reduction tool,
the two-dimensional subspace can be represented by its first and second principal
components. Independent component analysis is employed to convert the twodimensional
subspace into a skin image that represents skin areas due to melanin and
haemoglobin only.
In the skin image that represents skin areas due to melanin, vitiligous skin lesions are
identified as skin areas that lack melanin. Segmentation is performed to separate the
healthy skin and the vitiligous lesions. The difference in the vitiligous surface areas
between skin images before and after treatment will be expressed as a percentage of
repigmentation in each vitiligo lesion. This percentage will represent the repigmentation
progression of a particular body region.
Results of preliminary and pre-clinical trial study show that our vitiligo monitoring
system has been able to determine repigmentation progression objectively and thus
treatment efficacy on a shorter time cycle. An intensive clinical trial is currently
undertaken in Hospital Kuala Lumpur using our developed system.
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