Automatic Puncture System Based on NIR Image and Ultrasonic Image

In view of modern clinical treatment and care, venipuncture has a very important position, but in order to train a medical staff with high level skill of puncture need to spend a lot of time, human and material resources. For this reason, in this paper, an automatic system that can achieve venipuncture is proposed, which can replace the medical staff and achieve the puncture process. The automatic venipuncture system, combined with NIR imaging and ultrasound imaging technology, the overall plane information is obtained by NIR image, depth information and fine positioning of the plane information is obtained by ultrasound image. By way of image processing, the NIR image is enhanced and segmented, getting the spatial location of the vein. And the most suitable blood vessel segments were selected by piecewise straight fitting. Then the location ultrasonic probe should be placed is determined. Then the ultrasound image with the blood vessel in the vicinity of the longitudinal centreline can be obtained. All the information of blood vessel have been obtained, then the machine can be driven to achieve venipuncture.

[1]  Alvin I. Chen,et al.  Portable robot for autonomous venipuncture using 3D near infrared image guidance. , 2013, Technology.

[2]  Aaron Fenster,et al.  Design, calibration and evaluation of a robotic needle-positioning system for small animal imaging applications , 2007, Physics in medicine and biology.

[3]  A. N. Bashkatov,et al.  Optical properties of human skin, subcutaneous and mucous tissues in the wavelength range from 400 to 2000 nm , 2005 .

[4]  Yong Zhang,et al.  Commercialization of vein contrast enhancement , 2003, SPIE BiOS.

[5]  N. Sakai,et al.  Change in Blood Vessel Images of the Human Finger Using Near-Infrared Radiation While Compressing the Upper Arm , 2010 .

[6]  Yukio Yamada,et al.  Influence of Blood Glucose Level on the Scattering Coefficient of the Skin in Near-Infrared Spectroscopy , 2011 .

[7]  Dennis J Ernst Take the guesswork out of venipunctures. , 2009, MLO: medical laboratory observer.

[8]  Yan Zhang,et al.  In vivo real-time visualization of tissue blood flow and angiogenesis using Ag2S quantum dots in the NIR-II window. , 2014, Biomaterials.

[9]  Gunnar Lovhoiden,et al.  Clinical evaluation of vein contrast enhancement , 2002, SPIE BiOS.

[10]  Martin L. Yarmush,et al.  The System Design and Evaluation of a 7-DOF Image-Guided Venipuncture Robot , 2015, IEEE Transactions on Robotics.

[11]  Gunnar Lovhoiden,et al.  Design of a clinical vein contrast enhancing projector , 2001, SPIE BiOS.

[12]  Gunnar Lovhoiden,et al.  Enhancing the contrast of subcutaneous veins , 1999, Photonics West - Biomedical Optics.

[13]  Gabrielle Walsh Difficult Peripheral Venous Access: Recognizing and Managing the Patient at Risk , 2008 .

[14]  Gunnar Lovhoiden,et al.  Optimization of subcutaneous vein contrast enhancement , 2000, Photonics West - Biomedical Optics.