Abstract
Abstract In Hyperspectral imaging (HSI) applications in medicine a uniform illumination is used and the illuminated surface is recorded with a camera with spectral resolution. Unlike in tissue reflectance spectroscopy with fixed light source - detector distances, in HSI the contribution of the influence of different tissue layers to the absorption signal is poorly understood. In this work a Monte-Carlo simulation is implemented which simulates the specific HSI illumination and detector geometry. A four-layer tissue model with variable blood volume fraction and oxygen saturation is used. With 5 % blood volume fraction and 75 % oxygen saturation, SaO2, of surrounding tissue, saturation changes in 1 mm and 2 mm deep layers lead to a change in remission of up to 3 % and up to 1 % respectively. Changes in deeper layers are hardly detectable. Further simulations will be focused on different tissue models as the depth resolution is expected to vary with tissue parameters like blood volume fraction.
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