Healthy skin reflectance model

This pilot study is intended to investigate possibilities of skin nevus imaging using digital still image camera. The main objective is to develop method of dermatology images interpretation, which enables the looking on the skin lesions and nevus from the optical background of skin coloration. Kubelka-Munk calculation method for light transport and reflection from multilayered complex media is applied in modeling of light reflection spectra of skin. Calculation of model shows that red, green, blue and infrared colors lighting is satisfactory to access distribution of comparative estimates of the following skin parameters: volume fraction of melanin in epidermal layer, volume fraction of hemoglobin in dermal layer, presence of dermal melanin and thickness of papillary layer. Performance of image processing method on fourteen samples of images of common melanocytic nevi, dysphasic melanocytic nevi, Spitz nevus, thrombotic hemangioma and surrounding healthy skin were made. Skin spectral properties Understanding how light interacts with skin, can assist in designing physics based dermatological image processing. The key is understanding how light interacts with skin tissue. Skin consists of different layers with different spectral properties. Fig 1. Skin model and its physical view When incident light is applied to skin layer, the part of it absorbed…

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Review on skin lesion imaging, analysis and automatic classification

The goal of any imaging methodology used in dermatology is to diagnose melanoma in early stages because it depends on the effectiveness of treatment. Investigations shows, that early diagnosis is more than 90% curable and late is less than 50% [1]. The diagnosis and successful treatment are often supplemented with permanent monitoring of suspicious skin lesions. Doctor’s diagnosis is reliable, but this procedure takes lots of time, efforts. These routines can be automated. It could save lots of doctor’s time and could help to diagnose more accurately. Besides using computerized means there are excellent opportunity to store information with diagnostic information in order to use it for further investigations or creation of new methods of diagnosis. Skin lesion imaging methods We found that there are number of various imaging methods of skin lesions [2]. The simplest skin visualization method is photography. This method gives only top layer skin image. In order to get deeper layer image there is oil immersion used. It reduces reflections of surface and brightens the image of epidermis – the second skin layer.

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Skin lession boundary tracing algorithm

I found a Matlab to be a convenient tool which allows easily to trace boundaries of objects in a picture. So I adopted it to skin lesions. This can be used for automatic detection of skin irregularities and utilized to calculate lesion properties like the asymmetry of shape, or border irregularities, who can help in detecting melanoma. There are numerous investigations done, so I only put a few examples of how it looks. I will give you my source code so that you can try it on your own. Look at my results: 1) And it also finds the center of mass:

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Skin imaging methods for melanoma diagnosis

There are many skin image capture methodologies developed and used. Here is a short review of them: Dermatoscopic photography The deepest layer of skin can be reached – Papillary dermis Resolution – depends on the optical system View of skin – Horizontal The main disadvantage is reflections of light from skin surface – stratum cornea.   Dermatoscopic oil immersion photography The deepest layer of skin can be reached – Papillary dermis Resolution – depends on the optical system View of skin – Horizontal Reflections of light from skin surface are smaller because of oil used between camera optics and skin.

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Imaging system with four different wavelengths obtained from LEDs

In order to evaluate skin pigmentation in different skin layers, there is a special light adapter needed to take multispectral pictures of skin. As there are different optical properties of skin pigments, four different light sources have been chosen. blue λ= 470 nm – highly absorbed by epidermal melanin green λ= 576 nm – hemoglobin peak red  λ= 660nm – epidermal-dermal boundary IR λ= 865 nm – low absorption, sensitive to scattering to measure papillary dermis thickness. There was lighting source for “Nikon Coolpix E3100” digital camera developed to take multispectral images of skin. Making adapter The drawing of  lighting adapter The lighting adapter isn’t very hard to build. You need to make a circular PCB and solder LEDs with protective resistors. The PCB image:

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