Advisor:

Francisco E. Robles, Ph.D. (Georgia Institute of Technology and Emory University) 

Committee Members:  

Ahmet F. Coskun, Ph.D. (Georgia Institute of Technology and Emory University School of Medicine)   

Peng Qiu, Ph.D. (Georgia Institute of Technology and Emory University)  

Thomas K. Gaylord, Ph.D. (Georgia Institute of Technology)   

Wilbur A. Lam, M.D., Ph.D. (Georgia Institute of Technology and Emory University School of Medicine)   

Label-free Deep-Ultraviolet Microscopy: Accessible Molecular Imaging from Bench to Point of Care

Imaging with ultraviolet (UV) light (~ 200 - 400 nm) enables label-free molecular imaging due to the distinctive absorption and dispersion properties of several physiologically important, endogenous biomolecules in this spectral region. In addition, the shorter wavelength of UV light offers higher spatial resolution than conventional imaging systems that use visible light. Furthermore, advances in UV light sources and detectors have resulted in setups that enable contiguous imaging of live cells over long durations without significant photodamage.

This work aims to enhance the capabilities of deep-UV microscopy for accessible imaging of biological samples. Initially, we introduce a simple hyperspectral UV microscopy technique to extract quantitative absorption information from biological samples without prior knowledge of their optical properties. Following this, we employ multi-spectral deep-UV microscopy to quantify hemoglobin in red blood cells. Subsequently, we leverage recent advances in deep learning to develop an automated pipeline for label-free hematology analysis using single-wavelength UV microscopy images. In conjunction with a compact deep-UV microscope and custom microfluidic devices, this work can enable low-cost, efficient, and label-free hematology analysis within minutes, suitable for clinical, at-home, or low-resource settings. Additionally, we explore the development of a multispectral UV microscope for high-resolution, 3D tomographic imaging of cells.

Overall, this dissertation advances UV microscopy through improved instrumentation, analysis, and computational reconstruction, establishing it as an effective and economical label-free imaging tool for research, clinical, and point-of-care applications. We anticipate that the high-resolution molecular and structural information obtained from UV microscopy will further our understanding of fundamental biology and aid in disease diagnosis, monitoring, and treatment planning.