1 citations · 1 across the 4 of their papers we have counts for
4 papers
LaGuadia: Language-Guided Adaptive Distillation from Pathology Foundation Models
Gangsu Kim, Won-Ki Jeong
Pathology Foundation Models (PFMs) offer powerful Whole Slide Image (WSI) representations but suffer from massive computational costs. While Knowledge Distillation (KD) can create…
LanGuSTE: Language-Guided Coarse-to-Fine Patch Selection for Efficient Whole Slide Image Analysis
Yonghan Shin, Gangsu Kim, Won-Ki Jeong
Whole slide images (WSIs) in computational pathology pose a major computational challenge due to their gigapixel scale, often requiring tens to hundreds of thousands of high-resolu…
Clinical-grade Multi-Organ Pathology Report Generation for Multi-scale Whole Slide Images via a Semantically Guided Medical Text Foundation Model
Jing Wei Tan, SeungKyu Kim, Eunsu Kim +3
Vision language models (VLM) have achieved success in both natural language comprehension and image recognition tasks. However, their use in pathology report generation for whole s…
Reference-free Axial Super-resolution of 3D Microscopy Images using Implicit Neural Representation with a 2D Diffusion Prior
Kyungryun Lee, Won-Ki Jeong
Analysis and visualization of 3D microscopy images pose challenges due to anisotropic axial resolution, demanding volumetric super-resolution along the axial direction. While train…