Toward light-field interrogation of cell biology: Physics, computation, and systems
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Hua, Xuanwen
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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, such as wide-field microscopy, confocal microscopy, and structural illumination microscopy, produce orthographic views and acquire 3D information in a sequential or scanning fashion. In recent decades, the method of point-spread-function engineering has been rapidly developed, which allows for various unique features, such as non-diffracting beams for extended depth of focus, and axially variant beams for 3D imaging. On the other hand, 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. These abilities have revolutionized functional imaging with a cellular-level, milliseconds spatiotemporal resolution across a significantly large depth of focus. Due to the increasing need for new microscopic techniques that can provide high-throughput, high-spatiotemporal-resolution multi-color volumetric imaging of subcellular anatomies and dynamics, this thesis examines the physics, computation methods, and systems of light-field techniques, together with a comprehensive solution for microscopic wavefront modulation and the innovation of integrating flow cytometry and deep learning advances.
The main theme of this thesis revolves around three aspects. First, we established a point-spread-function-engineering strategy for depth-extended high-resolution volumetric imaging. Specifically, we develop the entire microscopic system, which includes the optical setup construction, the wave-optics model for numerical simulations, and the imaging acquisition and processing programs. We built the Fourier light-field microscope by implementing a microlens array to allow for single-shot 3D information retrieval. Second, we applied optofluidic devices to the imaging system for high-throughput, high-resolution volumetric imaging. We constructed the light-field flow cytometer for single-cell screening by integrating microfluidics into the Fourier light-field microscopy. 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. We effectively reduced reconstruction artifacts and accelerated the reconstruction process by incorporating deep neural networks for the task of 3D image reconstruction. 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.
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2023-12-13
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Dissertation