Calibration of a snapshot multispectral imaging system for detection of oxygen saturation
Description
There are many diseases in the eye including glaucoma, macular degeneration, and diabetic retinopathy in which early detection is crucial in order for treatments to be effective. Current detection methods are invasive and costly which lead to many of these diseases going undiagnosed. If not caught early, these diseases can seriously impair vision and even lead to complete blindness. The overreaching goal of our project is to develop a system that can detect these diseases early as well as help further understand the mechanisms that cause these diseases. To accomplish this goal, a snapshot multispectral imaging system was developed that is capable of capturing seven wavelengths simultaneously for the purpose of calculating oxygen saturation (OS). The main specific aim of this project is to determine if our system can detect changes in OS by capturing images of hemoglobin in vitro. It was found that there is a linear relationship with strong correlation (R2=0.91) between the OS our system detected and verified OS percentages from a blood oximeter. A linear equation was found from the data set that has a slope of 0.25 and y-intercept of -0.035. In this study, the stability of the system was also looked at by quantifying the variance between images of the same patient. A maximum of 4% error was found between images which is similar to other systems in the field. We also wanted to determine whether our in vitro correlation could be used to calculate OS percentages in vivo. The results were inconclusive because of a 23% standard deviation in the data but the hypothesis is that the in vitro correlation cannot be used directly in vivo because the backgrounds are different. The results of the main specific aim of this study proved that the concept of our design works in vitro which gives us confidence to continue to work towards a system that is clinically useful in vivo