BrightMind: An Integrated Hardware-Software Platform for Smart Photon Resolved Microscopy

Fluorescence laser-scanning microscopy (LSM) is the workhorse of life-science research, enabling low-invasive methods to probe live-cells with molecular sensitivity and high spatiotemporal resolution. Its impact has recently been expanded by photon-resolved microscopy, which uses single-photon array detectors to record photons one-by-one with precise spatial, temporal and spectral signatures. Analysis of this dataset yields unprecedented information, such as sub-diffraction images (down to the molecular scale), functional images, insights into molecular dynamics, and estimates of the microscope optical aberrations. These advances promise new biological discoveries and a new era of smart microscopy, where photon-level information drives experiments in real-time – e.g., correcting aberrations with adaptive optics. Despite this potential, photon-resolved microscopy remains confined to expert labs. Data complexity, fragmented hardware and offline software hinder accessibility, while evolving detectors and (AI-based) analysis quickly outpace existing solutions. BrightMind is the first customisable, upgradable, and integrated hardware-software platform for photon-resolved LSM. Built on system-on-chip FPGA technology, it unifies photon time-tagging with on-board processing, instantly transforming photon streams into interpretable results. This integration makes possible what was once impractical: real-time feedback LSM, plug-and-play use with any LSM system, and flexibility to evolve with new detectors and algorithms. BrightMind provides standardised outputs – from photon streams to pre-processed histograms, from application-ready results to RGB video frames – supporting researchers, fostering innovation by developers, and easing integration for microscopy and photonic devices manufacturers. By lowering barriers and streamlining workflows, BrightMind positions photon-resolved microscopy as the next generation of LSM, paving the way to smart and information-rich microscopy.