Graduation Semester and Year
2008
Language
English
Document Type
Thesis
Degree Name
Master of Science in Biomedical Engineering
Department
Bioengineering
First Advisor
Karel Zuzak
Abstract
We determine the penetration depth of near-infrared and visible light in a tissue phantom model using various image processing techniques and chemometrics and use these results to demonstrate the application of a multimodal hyperspectral imaging system for monitoring blood perfusion in amputation wounds. It is capable of performing a noninvasive, in vivo, quantitative analysis of human tissue in a clinical environment, in terms of the percent saturation of oxyhemoglobin. The instrument majorly consists of near-infrared and visible charge coupled devices (CCDs), lenses, liquid crystal tunable filters (LCTFs) for both the CCDs attached to their respective lenses, and a broad band light source. A 1% intralipid suspension, which mimics the skin-tissue interface and india ink, a good absorber of light are used to create the phantom model and experiments are done using this model to determine the penetration depth of near-infrared and visible light, by collecting hyperspectral image cubes using the hyperspectral instrument and analyzing it. Different methods of analyses are done on the image data cubes collected and the results prove that the near-infrared light penetrates deeper into tissues than visible. This result is used to demonstrate the ability of the hyperspectral imager to clinically monitor human lower limb amputation wounds and determine the perfusion of oxygenated blood in it. In other words, it can monitor amputation wounds based on the level of oxyhemoglobin saturation in the tissues.
Disciplines
Biomedical Engineering and Bioengineering | Engineering
License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Recommended Citation
Perumanoor, Tinsy John, "Visible Versus Near-infrared Light Penetration Depth Analysis In An Intralipid Suspension As It Relates To Clinical Hyperspectral Images" (2008). Bioengineering Theses. 190.
https://mavmatrix.uta.edu/bioengineering_theses/190
Comments
Degree granted by The University of Texas at Arlington