Effective vein visualization is vital for several clinical procedures, such as venous blood sampling and intravenous injection. Existing technologies using infrared devices or ultrasound technology are not suitable for daily medical care due to their equipment.
Now, researchers have devised a new regression-based vein visualization method. It uses conventional RGB images to assist in venipuncture procedures and clinical venous insufficiency diagnosis.
The researchers transformed the RGB images taken by digital cameras to spectral reflectance images using Wiener estimation. Subsequently, they applied multiple regression analysis to derive the relationship between spectral reflectance and the concentrations of pigments. They adopted Monte Carlo simulation to get prior information. Finally, they visualized vein patterns from the spatial distribution of pigments. The researchers performed light correction (adaptive gamma correction method ) and shading removal operations (algorithm) to minimize the effect of illumination on skin color.