Xuanwen Hua
BME PhD Defense Presentation
Date: 2023-11-10
Time: 10:00 am to 12:00 pm
Location / Meeting Link: EBB Krone Children's Healthcare of Atlanta Seminar Room / https://gatech.zoom.us/j/8709693823?pwd=U0kvVjRuQ2tLLzk5bUh0emY2OGthQT09
Committee Members:
Dr. Shu Jia (Advisor), Dr. Ahmet Coskun, Dr. Hang Lu, Dr. Peng Qiu, Dr. Francisco E. Robles
Title: Toward Light-Field Interrogation of Cell Biology: Physics, Computation, and Systems
Abstract:
Understanding how intracellular molecules and organelles are organized and dynamically mapped to functional activities requires tools for volumetric interrogation of single-cell systems with high spatiotemporal resolution and high throughput. Conventionally, optical microscopy techniques produce orthographic views and acquire 3D information in a sequential acquisition fashion. In recent years, the method of point-spread-function engineering has been rapidly developed, allowing for various unique features. Light-field microscopy, known as one of the point-spread-function engineering methods, simultaneously records both the 2D spatial and 2D angular information of the light field with a microlens array, allowing for the computational synthesis of the volume of a specimen from a single camera frame. This 4D imaging scheme offers ultrafast and volumetric acquisition, minimum photodamage for time-lapse observation, and high scalability and design flexibility. This dissertation examines the physics and develops new computation methods and systems of light-field techniques for the increasing need for new microscopic techniques that can provide high-throughput, high-spatiotemporal-resolution multi-color volumetric imaging of subcellular anatomies and dynamics. First, we established a point-spread-function-engineering strategy for depth-extended high-resolution volumetric imaging, including optical setup construction, numerical simulation using a wave-optics model, and developing imaging acquisition and processing programs. We then built the high-resolution Fourier light-field microscope for single-shot 3D information retrieval. Second, we applied optofluidic methods to the light-field imaging system for high-throughput, high-resolution volumetric imaging. We implemented stroboscopic illumination for motion-blur suppression and imaging throughput improvement. Finally, we enhanced the imaging capability of the Fourier light-field system with deep learning. This method effectively reduced reconstruction artifacts and accelerated the reconstruction process by incorporating deep neural networks for the task of 3D image reconstruction. Overall, the advancement offered by the Fourier light-field system presents a promising methodological pathway for broad cell-biological and translational investigations, with the potential for widespread adoption in various biomedical research fields.