Artificial intelligence-based real-time histopathology of gastric cancer using confocal laser endomicroscopy
Haeyon Cho, Damin Moon, So Mi Heo, Jinah Chu, Hyunsik Bae, Sangjoon Choi, Yubin Lee, Dongmin Kim, Yeong-Dae Jo, Kyuyoung Kim, Kyungmin Hwang, Dakeun Lee, Heung‐Kook Choi, Seokhwi Kim
Abstract
There has been a persistent demand for an innovative modality in real-time histologic imaging, distinct from the conventional frozen section technique. We developed an artificial intelligence-driven real-time evaluation model for gastric cancer tissue using confocal laser endomicroscopic system. The remarkable performance of the model suggests its potential utilization as a standalone modality for instantaneous histologic assessment and as a complementary tool for pathologists' interpretation.
Topics & Concepts
EndomicroscopyModality (human–computer interaction)HistopathologyConfocalCancerPathologyComputer scienceArtificial intelligenceMedicineMedical physicsRadiologyBiomedical engineeringOpticsInternal medicinePhysicsRadiomics and Machine Learning in Medical ImagingColorectal Cancer Screening and DetectionAI in cancer detection