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