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Abstract

Single-Molecule Orientation Localization Microscopy (SMOLM) measures the positions and orientations of single fluorophores precisely, approaching fundamental classical and quantum limits. However, a disadvantage of SMOLM is the time-consuming nature of its acquisition and reconstruction processes. In my thesis, I introduce an innovative framework that simplifies the detection and estimation algorithms used in SMOLM into a computationally efficient high-dimensional deconvolution algorithm. This framework extracts six-dimensional information of continuous biological structures from just a single camera image (i.e., a single shot). While this method is diffraction limited, unlike conventional SMOLM algorithms, it nevertheless offers accurate and precise estimations of the orientations of collections of molecules. Crucially, it is suitable for capturing dynamic changes in biological structures, thereby broadening its applicability in scientific investigations.

Document Type

Article

Author's School

McKelvey School of Engineering

Author's Department

Electrical and Systems Engineering

Class Name

Electrical and Systems Engineering Undergraduate Research

Date of Submission

1-2-2024

Available for download on Wednesday, January 01, 2025

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