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20222026
most citedCross-Field Transformer for Diabetic Retinopathy Grading on Two-field Fundus Images

2 citations · 7 across the 13 of their papers we have counts for

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8 papers · 1 filter

cs.CV2025

AOR: Anatomical Ontology-Guided Reasoning for Medical Large Multimodal Model in Chest X-Ray Interpretation

Qingqiu Li, Zihang Cui, Seongsu Bae +8

Chest X-rays (CXRs) are the most frequently performed imaging examinations in clinical settings. Recent advancements in Large Multimodal Models (LMMs) have enabled automated CXR in…

cs.CV2025

Text-Promptable Propagation for Referring Medical Image Sequence Segmentation

Runtian Yuan, Mohan Chen, Jilan Xu +6

Referring Medical Image Sequence Segmentation (Ref-MISS) is a novel and challenging task that aims to segment anatomical structures in medical image sequences (\emph{e.g.} endoscop…

cs.CV2024

Concept-Attention Whitening for Interpretable Skin Lesion Diagnosis

Junlin Hou, Jilan Xu, Hao Chen

The black-box nature of deep learning models has raised concerns about their interpretability for successful deployment in real-world clinical applications. To address the concerns…

cs.CV2024

QMix: Quality-aware Learning with Mixed Noise for Robust Retinal Disease Diagnosis

Junlin Hou, Jilan Xu, Rui Feng +1

Due to the complexity of medical image acquisition and the difficulty of annotation, medical image datasets inevitably contain noise. Noisy data with wrong labels affects the robus…

cs.CV20241 cited

Anatomical Structure-Guided Medical Vision-Language Pre-training

Qingqiu Li, Xiaohan Yan, Jilan Xu +6

Learning medical visual representations through vision-language pre-training has reached remarkable progress. Despite the promising performance, it still faces challenges, i.e., lo…

cs.CV2023

Enhanced Knowledge Injection for Radiology Report Generation

Qingqiu Li, Jilan Xu, Runtian Yuan +5

Automatic generation of radiology reports holds crucial clinical value, as it can alleviate substantial workload on radiologists and remind less experienced ones of potential anoma…