Hyperspectral skin analysis
In a case study for the detection of collagen and the analysis of the spectral behavior of skin a Firefleye Q285 QE was adapted to the measurement port of an Axiophot from Zeiss, a scientific microscope. The camera afterwards needed to be calibrated mounted on the microscope. Since the interna optics of the Axiophot filter Near Infrared radiation the measurements where performed in the wavelength range of 450-750 nm with 75 spectral bands.
The spatial resolution was 1MP, the recordings were made in transmitted light with an integration time of 5 and 10 ms. The frame rate was set to 15Hz.
Hyperspectral measurement of collagen
Collagen is a group of naturally occurring proteins found in humans and animals. In the human body the collagen content is more than 30% of the total weight of all proteins. It is a very important component of connective tissue and of the skin.
In figure 1 you can see the software interface of the Cube Pilot. At the right-hand side is a recording of collagen taken with the Firefleye Q285 QE. In order to detect each pixel showing collagen within that image one characteristic point was selected, which was identified as collagen. The software is then able to identify similar spectra automatically. All those pixels are marked in red in that image.
Analysing skin structure
Skin is the most versatile organ. It serves as a barrier to the outside, a protection from environmental influences and it takes over important functions in the realm of metabolism and immunology. It consists of three layers: the epidermis, the dermis and the subcutaneous tissue (or hypodermis).
The image on the left-hand side in figure 2 shows a recording of skin taken with the Q285 QE. The epidermis is recognizable in the upper right, the dermis is located directly underneath and in the lower left the subcutaneous tissue is depicted. Several points were chosen in this recording. For these issues, it was measured how much light is reflected at the required wavelength. On the right-hand side a number of graphs are represented, each provided for the selected areas. These graphs describe the reflectance and the spectral deviations in the range of 450-750 nm.
In figure 3 three bands were used to generate a RGB false-color image. The intensity for Red is represented by the intensity of reflectance at 510nm. For Green the ratio of the squared wavelengths (510-470 nm) and (510+470 nm). In Blue the reflectance value of 686nm is represented.
Depending on the setting of the wavelenths it is possible to generate different false-color plots. In these false-color plots various elements can be highlighted. By this we can take a look deep into specific issues for the microscopic diagnosis of cells. The sorting of similar spectra always takes place in the same way. One characteristic point can be selected and the software identifies similar spectra automatically, showing the high potential value of hyperspectral information for medical analyses.
We would like to thank Dr. Jochen K. Lennerz for the friendly collaboration and supply of the measurement results.