White light imaging (WLI) remains indispensable as the standard of care during surgery and therapy, from ophthalmoscopy to endoscopy. The primary purpose of WLI is to guide the operator by faithfully replicating the human vision system. Yet in doing so, valuable biochemical information about the tissue is subsequently lost, with tissue contrast perceived solely by the human eye. Multispectral imaging (MSI) captures spatial information across a number of spectral (or color) bands. Selecting spectral bands to target specific spectral biomarkers could enhance the sensitivity and specificity of imaging diagnostic methods. Multispectral filter arrays (MSFAs) based on thin-film optical components can be monolithically integrated with image sensors and are proposed as a key enabler for MSI in medical imaging. In this presentation, Dr. Sawyer will discuss ongoing work including computational methods to design MSFAs, fabricate techniques for manufacturing, and preliminary prototypes of MSFAs for medical imaging applications including cancer diagnosis and screening.
Travis Sawyer is an assistant professor of optical sciences and health sciences. He received his BS in optical sciences from the UA (2017) before attending the University of Cambridge to receive his MPhil in physics (2018). He then returned to the UA pursue his PhD in optical sciences (2021) where he focused on developing novel imaging techniques for ovarian cancer detection. After graduating, he joined the faculty at the College of Optical Sciences to establish the Biomedical Optics and Optical Measurement Lab. His research interests include gastrointestinal cancer detection, where he develops endoscopes incorporating optical coherence tomography, fluorescence imaging, and other novel imaging modalities, with a focus on image analysis through machine learning techniques. He has extensive experience in animal and human studies, as well as optical design and has collaborated with the University of Cambridge to develop endoscopes using hyperspectral and phase imaging. Previously, he developed visual recognition software for detailed image capture, enabling discoveries in astronomy, art preservation, and the biomedical sciences. Travis is also a strong supporter of science outreach, regularly organizing and supporting efforts to educate the community and encourage careers in science.