Development of a multi-scanner facility for data acquisition for digital pathology artificial intelligence

Abstract

Abstract Whole slide imaging (WSI) of pathology glass slides with high-resolution scanners has enabled the large-scale application of artificial intelligence (AI) in pathology, to support the detection and diagnosis of disease, potentially increasing efficiency and accuracy in tissue diagnosis. Despite the promise of AI, it has limitations. “Brittleness” or sensitivity to variation in inputs necessitates that large amounts of data are used for training. AI is often trained on data from different scanners but not usually by replicating the same slide across scanners. The utilisation of multiple WSI instruments to produce digital replicas of the same glass slides will make more comprehensive datasets and may improve the robustness and generalisability of AI algorithms as well as reduce the overall data requirements of AI training. To this end, the National Pathology Imagine Cooperative (NPIC) has built the AI FORGE ( F acilitating O pportunities for R obust G eneralisable data E mulation), a unique multi-scanner facility embedded in a clinical site in the NHS to (a) compare scanner performance and (b) replicate digital pathology image datasets across WSI systems. The NPIC AI FORGE currently comprises 15 scanners from 9 manufacturers. It can generate approximately 4000 WSI images per day (approximately 7Tb of image data). This paper describes the process followed to plan and build such a facility.

Ähnliche Arbeiten