Xuanwen Hua

BME PhD Proposal

Date: Thursday, July 22nd

Time: 12pm-2pm

Meeting Link: Zoom / https://us02web.zoom.us/j/9933642230?pwd=VEFmUlFZeWpWRTRPUTRITldxdlpVZz09  
(Meeting ID: 993 364 2230, Passcode: hxw2021 )

Committee Members:

Dr. Shu Jia (Advisor)

Dr. Ahmet Coskun

Dr. Hang Lu

Dr. Peng Qiu

Dr. Francisco Robles

Title: High-Resolution, High-Throughput, and Machine-Intelligent Single-Cell Imaging with Microfluidic Fourier Light-Field Microscopy (μ-FLFM)

Abstract: Observation and interrogation of cellular structures and functions at a high spatiotemporal resolution and throughput have been playing a significant role in comprehending cell physiology, development, and pathology. Recent years have witnessed the emergence of advanced imaging techniques, which have revolutionized a wide range of single-cell studies. Nevertheless, there has been a persistent need of new imaging technology to accommodate to the bloom of biological discoveries. Here, the Ph.D. Candidate proposes to develop a microfluidic Fourier Light-Field Microscopy (μ-FLFM) system, enhanced by deep learning, for high-resolution, high-throughput volumetric cell imaging. Built upon the Candidate’s prior training and accomplishments, the objectives of the project are to establish a PSF-engineering strategy for depth-extended high-resolution volumetric imaging with wavefront modulation and aperture partitioning, apply optofluidics to the imaging system for high-throughput high-resolution volumetric imaging, and enhance the optofluidic imaging capability of the system with deep learning. The Candidate anticipates this innovative imaging system to provide a multiplexed methodology for investigating subcellular anatomy, function and cell-to-cell variability, paving a promising pathway for broad single-cell investigations and technological breakthroughs.