2 citations · 2 across the 4 of their papers we have counts for
4 papers
OCELOT 2023: Cell Detection from Cell-Tissue Interaction Challenge
JaeWoong Shin, Jeongun Ryu, Aaron Valero Puche +21
Pathologists routinely alternate between different magnifications when examining Whole-Slide Images, allowing them to evaluate both broad tissue morphology and intricate cellular d…
SCORPION: Addressing Scanner-Induced Variability in Histopathology
Jeongun Ryu, Heon Song, Seungeun Lee +4
Ensuring reliable model performance across diverse domains is a critical challenge in computational pathology. A particular source of variability in Whole-Slide Images is introduce…
OCELOT: Overlapped Cell on Tissue Dataset for Histopathology
Jeongun Ryu, Aaron Valero Puche, JaeWoong Shin +9
Cell detection is a fundamental task in computational pathology that can be used for extracting high-level medical information from whole-slide images. For accurate cell detection,…
Interactive Multi-Class Tiny-Object Detection
Chunggi Lee, Seonwook Park, Heon Song +5
Annotating tens or hundreds of tiny objects in a given image is laborious yet crucial for a multitude of Computer Vision tasks. Such imagery typically contains objects from various…