Date of Graduation
5-2024
Document Type
Thesis
Degree Name
Bachelor of Science in Biomedical Engineering
Degree Level
Undergraduate
Department
Biomedical Engineering
Advisor/Mentor
Muldoon, Timothy J.
Abstract
Colorectal cancer is a common form of cancer, and is heavily researched in murine models. Colonoscopies are often performed in clinical settings to assess the health of the colon, as well as locate and assess the severity of tumors in a non-invasive way. As the quality of the images is dependent on the colonic environment and the light available, it is important to ensure the accuracy of the images via a normalization algorithm. The RGB images procured from these colonoscopies have great potential as a diagnostic tool for physicians, as varying scales of discoloration is common in hypoxic tissue. While ratios of R to G, G to B, and R to B have been explored in relation to hypoxia in skin, brain, and ocular cancers, it has yet to be explored in the context of colorectal cancer. This was explored through the validation of the colonoscopic setup with a standard color checker, which demonstrated that there was significant variation in RGB values depending on distance and lighting level. Polyps of interest were then segmented in MATLAB and analyzed for their RGB values. The relation between RGB ratios and StO2 and Hb concentrations (tissue oxygenation DRS measures) is unclear, as they differed between polyps 4 and 7 in mouse 331 from AUP 23012. While polyp 4 appeared to have all three measures reaching a maximum at week 3 and decreasing for the remainder of the weeks, polyp 7 values all stayed relatively constant with little change. However, with a larger data set and analyzing more mice from the study, there is potential to note concrete trends.
Keywords
Colorectal cancer; RGB Imaging; Endoscopy; Colonoscopy
Citation
Nischal, N. (2024). Detection of Hypoxia via RGB Imaging. Biomedical Engineering Undergraduate Honors Theses Retrieved from https://scholarworks.uark.edu/bmeguht/144
