Hyperspectral venous image quality assessment for optimum illumination range selection based on skin tone characteristics

Shahzad, Aamir and Saad, N.M. and Nicolas, Walter and Malik, Aamir Saeed and Meriaudeau, Fabrice (2014) Hyperspectral venous image quality assessment for optimum illumination range selection based on skin tone characteristics. [Citation Index Journal]



Background Subcutaneous veins localization is usually performed manually by medical staff to find suitable vein to insert catheter for medication delivery or blood sample function. The rule of thumb is to find large and straight enough vein for the medication to flow inside of the selected blood vessel without any obstruction. The problem of peripheral difficult venous access arises when patient’s veins are not visible due to any reason like dark skin tone, presence of hair, high body fat or dehydrated condition, etc. Methods To enhance the visibility of veins, near infrared imaging systems is used to assist medical staff in veins localization process. Optimum illumination is crucial to obtain a better image contrast and quality, taking into consideration the limited power and space on portable imaging systems. In this work a hyperspectral image quality assessment is done to get the optimum range of illumination for venous imaging system. A database of hyperspectral images from 80 subjects has been created and subjects were divided in to four different classes on the basis of their skin tone. In this paper the results of hyper spectral image analyses are presented in function of the skin tone of patients. For each patient, four mean images were constructed by taking mean with a spectral span of 50 nm within near infrared range, i.e. 750–950 nm. Statistical quality measures were used to analyse these images. Conclusion It is concluded that the wavelength range of 800 to 850 nm serve as the optimum illumination range to get best near infrared venous image quality for each type of skin tone.

Item Type:Citation Index Journal
Impact Factor:1.746
Subjects:Q Science > Q Science (General)
T Technology > T Technology (General)
Academic Subject One:Biomedical Image Processing
Departments / MOR / COE:Centre of Excellence > Center for Intelligent Signal and Imaging Research
Departments > Electrical & Electronic Engineering
Research Institutes > Institute for Health Analytics
ID Code:11376
Deposited By: Dr Aamir Saeed Malik
Deposited On:28 Apr 2015 02:54
Last Modified:28 Apr 2015 02:54

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