High-contrast subcutaneous vein detection and localization using multispectral imaging.

Multispectral imaging has shown promise in subcutaneous vein detection and localization in human subjects. While many limitations of single-wavelength methods are addressed in multispectral vein detection methods, their performance is still limited by artifacts arising from background skin reflectance and optimality of postprocessing algorithms. We propose a background removal technique that enhances the contrast and performance of multispectral vein detection. We use images acquired at visible wavelengths as reference for removing skin reflectance background from subcutaneous structures in near-infrared images. Results are validated by experiments on human subjects.