Wenhao liu
BME PhD Defense Presentation

Date: 2024-03-19
Time: 11:00 AM-1:00 PM
Location / Meeting Link: Location/Meeting Link: Conference room 1117-1118 at Marcus Nano Building, https://us05web.zoom.us/j/81790327682?pwd=3x8vuxUbm4iakTInMPk3xa9rTECCTt.1

Committee Members:
Shu Jia, PhD (Advisor) Shuichi Takayama PhD Francisco Robles, PhD Denis Tsygankov PhD Shuyi Nie, PhD


Title: Fourier light-field microscopy: Design, optimization, and applications

Abstract:
Visualizing diverse anatomical and functional traits that span many spatio-temporal scales with high spatio-temporal resolution provides insights into the fundamentals of biological systems. Light-field microscopy (LFM) has recently emerged as a scanning-free, scalable method allowing for high-speed, volumetric imaging ranging from single-cell specimens to the mammalian brain. However, the nonuniform axial sampling and spatially variant PSF of LFM limit its imaging depth and make its computational cost unbearable, prohibiting LFM from broader applications. To address the challenge, in this work, we reported Fourier LFM (FLFM), a system that processes light-field information through the Fourier domain, substantially overcomes the drawbacks of LFM, and realized fast, multicolor, 3D imaging with enhanced spatial resolution and extended imaging depth. In detail, we first established a complete theoretical and algorithmic framework of FLFM for light propagation, image formation, system characterization, volume reconstruction, and a generic principle for instrument design. Next, we systematically validated the model for FLFM on a prototype system by high-resolution, artifact-free imaging of various caliber and biological samples and developed two FLFM systems based on the design protocol for fast, volumetric, high-resolution live imaging respectively on whole cell and entire organoids and demonstrated their imaging capacities by observing subcellular activities of organelles and quick response of organoids to external cues respectively. Then, we optimized the software of FLFM, introducing wFLFM, an approach that enhances the lateral resolution of FLFM by two- to three-fold through a hybrid imaging scheme, and PEARL, an algorithm using linear search to accelerate the reconstruction via 3D R-L deconvolution by reducing the iteration times. In the end, we improved the hardware of our FLFM system to enable simultaneous two-color FLFM imaging. We combined it with specific design programs to broaden the application of FLFM in multiple biomedical studies, such as interrogating the mechanisms of cancer invasion, drug screening for cardiac treatment, in vivo quantitative cardiovascular evaluation, and recording locomotion-related neural signals. We anticipate FLFM to be a potent tool for imaging diverse phenotypic and functional information spanning broad molecular, cellular, and tissue systems.