Abstract
Fluorescence Lifetime Imaging Microscopy (FLIM) is a powerful tool for biomedical re- search. It leverages fluorescence of biological samples to visualize and characterize biological dynamics and molecular interactions. FLIM utilizes fluorescence lifetime, the average time a molecule stays in its excited state after absorbing a photon, to investigate the dynamics of biological samples.
Ultra-fast and precise (ps-ns) timing fluorescence acquisition techniques suffer from different trade-offs. Some methods suffer from high dead times, decreased accuracy in fluorescence lifetime calculations, and high data volumes and transfers. Finding a new method that can provide the best performance while experiencing low dead times, adequate temporal resolution, and manageable data volumes, is integral to improving the functionality of FLIM. Single- and multi-photon peak event detection (SPEED) is a computational photon-counting method that has low dead times and high accuracy in fluorescence lifetime calculations. However, since the analog signal is digitized at high rates (5-10 GS/s), it suffers from the drawbacks that come with high data volumes, such as long transfer and processing times. To combat this, a data compression scheme on our field-programmable gate array (FPGA) is introduced and explored to reduce the amount of data transfers between our FPGA and CPU. Most of the data passed from the FPGA and CPU are zeros (95-99%) and the goal of the compression algorithm is to compress consecutive all zero data transfers to limit the total amount of data passed through the system. A three-state FSM was designed to implement the algorithm. The compression algorithm was analyzed in Verilog simulation and matched MATLAB simulations.
Committee Chair
Janet Sorrells
Committee Members
Matthew Lew Roger Chamberlain
Degree
Master of Science (MS)
Author's Department
Electrical & Systems Engineering
Document Type
Thesis
Date of Award
Winter 12-17-2025
Language
English (en)
Author's ORCID
https://orcid.org/0000-0001-8629-7017
Recommended Citation
Onyeador, Chibueze, "FPGA-Accelerated Computational Photon Counting" (2025). McKelvey School of Engineering Theses & Dissertations. 1302.
https://openscholarship.wustl.edu/eng_etds/1302
Included in
Electromagnetics and Photonics Commons, VLSI and Circuits, Embedded and Hardware Systems Commons