A two-layer GPU-accelerated inverse adding-doubling algorithm was applied to hyperspectral images of a forearm to extract skin optical properties before, during, and after a cuff-test. Calculated and measured skin reflectance show great agreement.
Significance: Hyperspectral imaging (HSI) has emerged as a promising optical technique. Besides optical properties of a sample, other sample physical properties also affect the recorded images. They are significantly affected by the sample curvature and sample surface to camera distance. A correction method to reduce the artifacts is necessary to reliably extract sample properties.
Aim: Our aim is to correct hyperspectral images using the three-dimensional (3D) surface data and assess how the correction affects the extracted sample properties.
Approach: We propose the combination of HSI and 3D profilometry to correct the images using the Lambert cosine law. The feasibility of the correction method is presented first on hemispherical tissue phantoms and next on human hands before, during, and after the vascular occlusion test (VOT).
Results: Seven different phantoms with known optical properties were created and imaged with a hyperspectral system. The correction method worked up to 60 deg inclination angle, whereas for uncorrected images the maximum angles were 20 deg. Imaging hands before, during, and after VOT shows good agreement between the expected and extracted skin physiological parameters.
Conclusions: The correction method was successfully applied on the images of tissue phantoms of known optical properties and geometry and VOT. The proposed method could be applied to any reflectance optical imaging technique and should be used whenever the sample parameters need to be extracted from a curved surface sample.
A novel LED based light source with a high degree of modularity is resented as a means of illumination in a hyperspectral imaging system, employing multiple LED panes with different wavelengths. We report on first results and experience gained using such illumination in a large area hyperspectral imaging system.
Curvature and height corrections were made on hyperspectral images in order to reduce intensity dependence on distance and inclination. The corrections were made by Lambertian cosine law and measured 3D surface of the sample. Image of homogeneous phantom appeared significantly more homogeneous after correction.
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