5 papers
Concept-Guided Noisy Negative Suppression for Zero-Shot Classification and Grounding of Chest X-Ray Findings
Chenyu Lian, Hong-Yu Zhou, Chun-Ka Wong +1
Vision-language alignment using chest X-rays and radiology reports has emerged as an advanced paradigm for zero-shot classification and grounding of chest X-ray findings. However,…
Evidential Reasoning Advances Interpretable Real-World Disease Screening
Chenyu Lian, Hong-Yu Zhou, Jing Qin
Disease screening is critical for early detection and timely intervention in clinical practice. However, most current screening models for medical images suffer from limited interp…
BenchReAD: A systematic benchmark for retinal anomaly detection
Chenyu Lian, Hong-Yu Zhou, Zhanli Hu +1
Retinal anomaly detection plays a pivotal role in screening ocular and systemic diseases. Despite its significance, progress in the field has been hindered by the absence of a comp…
Efficient Medical Vision-Language Alignment Through Adapting Masked Vision Models
Chenyu Lian, Hong-Yu Zhou, Dongyun Liang +2
Medical vision-language alignment through cross-modal contrastive learning shows promising performance in image-text matching tasks, such as retrieval and zero-shot classification.…
CorBenchX: Large-Scale Chest X-Ray Error Dataset and Vision-Language Model Benchmark for Report Error Correction
Jing Zou, Qingqiu Li, Chenyu Lian +4
AI-driven models have shown great promise in detecting errors in radiology reports, yet the field lacks a unified benchmark for rigorous evaluation of error detection and further c…