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…
Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder
Biagio Brattoli, Jack Shi, Jongchan Park +3
Identifying actionable driver mutations in non-small cell lung cancer (NSCLC) can impact treatment decisions and significantly improve patient outcomes. Despite guideline recommend…
Generalizing AI-driven Assessment of Immunohistochemistry across Immunostains and Cancer Types: A Universal Immunohistochemistry Analyzer
Biagio Brattoli, Mohammad Mostafavi, Taebum Lee +14
Despite advancements in methodologies, immunohistochemistry (IHC) remains the most utilized ancillary test for histopathologic and companion diagnostics in targeted therapies. Howe…
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,…