Engineering a Data Processing Pipeline for an Ultra-Lightweight Lensless Fluorescence Imaging Device with Neuronal-Cluster Resolution

• Main Authors: Yu, Zihao, Guinto, Mark Christian S.G., Lim, Brian Godwin S., Tan, Renzo Roel P, Yoshimoto, Junichiro, Ikeda, Kazushi, Ohta, Yasumi, Ohta, Jun
• Format: text
• Published: Archīum Ateneo 2023
• Subjects: CMOS-based device; Data mining; Fluorescence imaging; Noise reduction; Principal component analysis; Biomedical; Medicine and Health Sciences
• Online Access: https://archium.ateneo.edu/qmit-faculty-pubs/17; https://doi.org/10.1007/s10015-023-00875-x
• Institution: Ateneo De Manila University

In working toward the goal of uncovering the inner workings of the brain, various imaging techniques have been the subject of research. Among the prominent technologies are devices that are based on the ability of transgenic animals to signal neuronal activity through fluorescent indicators. This pa...