4 papers
XFlow: A Workflow Model for Instruction-Guided Lesion Segmentation in Chest X-rays
Geon Choi, Hangyul Yoon, Hyunki Park +2
Existing text-guided segmentation models in the medical domain cover only a narrow set of anatomical structures and lesions in chest X-rays (CXRs), and most of them assume that the…
CheXpercept: A Benchmark for Evaluating Expert-Level Lesion Perception in Chest X-rays
Geon Choi, Hangyul Yoon, Nalee Kim +5
The evaluation of vision-language models (VLMs) for chest X-ray (CXR) analysis has largely been limited to disease-presence classification without visual grounding. Such evaluation…
A Guideline-Aware AI Agent for Zero-Shot Target Volume Auto-Delineation
Yoon Jo Kim, Wonyoung Cho, Jongmin Lee +7
Delineating the clinical target volume (CTV) in radiotherapy involves complex margins constrained by tumor location and anatomical barriers. While deep learning models automate thi…
Instruction-Guided Lesion Segmentation for Chest X-rays with Automatically Generated Large-Scale Dataset
Geon Choi, Hangyul Yoon, Hyunju Shin +4
The applicability of current lesion segmentation models for chest X-rays (CXRs) has been limited both by a small number of target labels and the reliance on complex, expert-level t…