Ambient, real-time digitization and datafication of glass slide microscopy towards AI-at-the-microscope

Abstract

Pathology remains central to clinical diagnosis, yet adoption of digital pathology is constrained by financial, operational, and workflow burdens of fully digital infrastructure. We introduce HistoCAM, a platform for ambient, real-time datafication and digitization of glass-slide microscopy that preserves microscope workflows. A 31-megapixel, high space-bandwidth-time-product camera and custom software application stream and composite the pathologist’s eyepiece view, passively generating multi-resolution images from 2X to 40X while recording magnification use, search paths, and dwell times. These outputs provide immediate workflow uplift through digital annotation, measurement, quality assurance, and real-time integration of configurable AI tools. Simultaneously, HistoCAM links image content with expert interaction data and supports rapid generation of annotated, pre-embedded training data during routine slide review. By converting routine microscopy into an AI-ready data stream without requiring additional acquisition steps, HistoCAM provides a practical bridge to computational pathology while creating process-aware datasets that capture how pathologists examine and interpret tissue.