Beyond Multiple Instance Learning: Full Resolution All-In-Memory End-To-End Pathology Slide Modeling

arXiv:2403.04865v1 Announce Type: cross
Abstract: Artificial Intelligence (AI) has great potential to improve health outcomes by training systems on vast digitized clinical datasets. Computational Pathology, with its massive amounts of microscopy image data and impact on diagnostics and biomarkers, is at the forefront of this development. Gigapixel pathology slides pose a unique challenge due to their enormous size and are usually divided into tens of thousands of smaller tiles for analysis. This results in a discontinuity in the machine learning …

abstract artificial artificial intelligence arxiv beyond clinical computational cs.cv data datasets development diagnostics eess.iv health image image data impact in-memory instance intelligence massive memory microscopy modeling multiple pathology slides systems training type vast