Quantitative Imaging and Informatics Laboratory (QuIIL)

AUGUST is a sequential QA framework for gastric pathology that mimics pathologist reasoning. By explicitly modeling hierarchical dependencies, it outperforms SOTA models in accuracy and consistency across 23k WSIs.

[EMA4MICCAI 2026] Test-Time Instance Selection for Improved Whole Slide Image Analysis

HEXST: Hexagonal Shifted-Window Transformer for Spatial Transcriptomics Gene Expression Prediction

TaxoMIL: Taxonomy-Constrained Learning for Hierarchical Whole Slide Image Analysis [ECCV 2026]

COAST: Context-Aware Differential Learning for Gene Expression Prediction in Spatial Transcriptomics

BiStainDiff: Bidirectional Stain Diffusion Model

GastUJB is a comprehensive, internally curated gastric pathology dataset collected at the Catholic University of Korea Uijeongbu St. Mary’s Hospital (2014–2023). It serves as a primary cohort for defining diagnostic taxonomies and evaluating fine-grained computational pathology tasks.

Normal and Abnormal Pathology Knowledge-Augmented Vision-Language Model for Anomaly Detection in Pathology Images