Multispectral venous images analysis for optimum illumination selection

Intravenous (IV) catheterization is the most important phase in medical practices of daily life. It is hard to localize veins in patients who have deep veins, minor age or dark skin; hence multiple attempts become indispensable for proper catheterization in such cases. Near Infrared (NIR) Imaging allow to visualize the veins underneath the skin of persons having non-visibility of veins problem. This paper reports the pre-selection of illuminants that ensure best veins/tissues contrast for patients having different skin tone. The sample subjects have been divided in four different classes based on the Luminance value of their skin tone in order to extract the best illuminant wavelengths range for each class. A multispectral approach has been used which provides the flexibility of wavelength range from visible to NIR (380 to 1040nm). The veins/tissue reflectance contrast obtained helps in determining the best wavelengths range where the contrast is maximum for each of the four classes. Using these results, we are planning to build a prototype system which can automatically select the illuminants based on different physiological characteristics of a subject.

[1]  D. Boas,et al.  Non-invasive neuroimaging using near-infrared light , 2002, Biological Psychiatry.

[2]  J. Stockman,et al.  Veinlite Transillumination in the Pediatric Emergency Department: A Therapeutic Interventional Trial , 2009 .

[3]  Charles A. DiMarzio,et al.  Medical Imaging Techniques Combining Light and Ultrasound , 2003 .

[4]  Kenneth W. Tobin,et al.  3D and multispectral imaging for subcutaneous veins detection. , 2009 .

[5]  J. Niederhauser,et al.  Real-time biomedical optoacoustic imaging , 2004 .

[6]  Gunnar Lovhoiden,et al.  Prototype vein contrast enhancer , 2004, SPIE BiOS.

[7]  Bruce J. Tromberg,et al.  Face Recognition in Hyperspectral Images , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Izumi Nishidate,et al.  Visualizing depth and thickness of a local blood region in skin tissue using diffuse reflectance images. , 2007, Journal of biomedical optics.

[9]  Lynn Hadaway,et al.  Infiltration and extravasation. , 2007, The American journal of nursing.

[10]  A J Barton,et al.  Improving patient outcomes through CQI: vascular access planning. , 1998, Journal of nursing care quality.

[11]  Biomedical Photoacoustic Imaging Using Gas-coupled Laser Acoustic Detection , 2013 .

[12]  Kenneth W. Tobin,et al.  Combining near-infrared illuminants to optimize venous imaging , 2007, SPIE Medical Imaging.

[13]  Hua-bei Jiang,et al.  Photoacoustic Imaging: An Emerging Optical Modality in Diagnostic and Theranostic Medicine , 2011 .

[14]  Dinh Tuan Vo Biomedical photonics handbook , 2003 .