Improving flat fluorescence microscopy in scattering tissue through deep learning strategies

Two-Photon and Multiphoton Microscopy in Anterior Segment Diseases of the Eye

Two-photon excitation microscopy (TPM) and multiphoton fluorescence microscopy (MPM) are advanced forms of intravital high-resolution functional microscopy techniques that allow for the imaging of dynamic molecular processes and resolve features of the biological tissues of interest. Due to the cornea's optical properties and the uniquely accessible position of the globe, it is possible to image cells and tissues longitudinally to investigate ocular surface physiology and disease. MPM can also be used for the in vitro investigation of biological processes and drug kinetics in ocular tissues. In corneal immunology, performed via the use of TPM, cells thought to be intraepithelial dendritic cells are found to resemble tissue-resident memory T cells, and reporter mice with labeled plasmacytoid dendritic cells are imaged to understand the protective antiviral defenses of the eye. In mice with limbal progenitor cells labeled by reporters, the kinetics and localization of corneal epithelial replenishment are evaluated to advance stem cell biology. In studies of the conjunctiva and sclera, the use of such imaging together with second harmonic generation allows for the delineation of matrix wound healing, especially following glaucoma surgery. In conclusion, these imaging models play a pivotal role in the progress of ocular surface science and translational research.

Deep Learning Empowered Fresnel-based Lensless Fluorescence Microscopy. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023;2023:1-4. [PMID: 38082985 DOI: 10.1109/embc40787.2023.10339990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Miniaturized fluorescence microscopy has revolutionized the way neuroscientists study the brain in-vivo. Recent developments in computational lensless imaging promise a next generation of miniaturized microscopes in lensless fluorescence microscopy. We developed a microscope prototype using an optimized Fresnel amplitude mask. While many lensless imaging modalities have reported excellent performance using Deep Learning (DL) approaches, DL application in fluorescence imaging has been left untouched. We generated a computational dataset based on experimental system calibration to evaluate DL capabilities on biological cell morphologies. We show that our DL-assisted microscope can provide high-quality imaging with a structural similarity index of 89%. The least absolute error was decreased by 63% using the DL-assisted method compared with the classical models. The state-of-the-art performance of this prototype enhances the expected potential of amplitude masks in lensless microscopy applications, which are critical for robust in-vivo flat microscopy with engineered image sensors.Clinical Relevance- This study aids in advancing miniaturized fluorescence microscopy, which greatly impacts long-term brain circuit and disease studies in freely moving animal models.