Real-Time Non-invasive Imaging of Subcutaneous Blood Vessels

Automatic, fast and accurate extraction of the blood vessel is an important task in the image-aided diagnosis of disease. In this paper, we describe a novel superficial vessel imaging and projecting system. First, the superficial vessel of human arm is captured by NIR imaging technique, and then three pre-processing algorithms, including hair removal, non-uniform illumination correction and vessel enhancement, are developed to strengthen the vessel image. Second, a model-based binarization method is proposed to detect vessel-like structures. And then the mathematic morphological and connected component refinement methods are integrated to remove small vessel noises. Experimental results demonstrate that our system can imaging superficial vessels on real-time. The proposed system does not need any human interaction, which hence can be used in clinical venipuncture practices.