18 citations · 44 across the 14 of their papers we have counts for
15 papers
Detecting Clinical Hallucinations in LVLMs via Counterfactual Visual Grounding Uncertainty
Xiao Song, Haonan Qin, Zhaoxu Zhang +3
Large vision-language models (LVLMs) are increasingly used for clinical image understanding, yet they remain vulnerable to \emph{hallucinations}--producing textual findings or attr…
Generative Data-engine Foundation Model for Universal Few-shot 2D Vascular Image Segmentation
Rongjun Ge, Xin Li, Yuxing Liu +8
The segmentation of 2D vascular structures via deep learning holds significant clinical value but is hindered by the scarcity of annotated data, severely limiting its widespread ap…
Multimodal Feature Prototype Learning for Interpretable and Discriminative Cancer Survival Prediction
Shuo Jiang, Zhuwen Chen, Liaoman Xu +6
Survival analysis plays a vital role in making clinical decisions. However, the models currently in use are often difficult to interpret, which reduces their usefulness in clinical…
Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network
Tao Chen, Dan Zhang, Da Chen +7
Choroidal neovascularization (CNV), a primary characteristic of wet age-related macular degeneration (wet AMD), represents a leading cause of blindness worldwide. In clinical pract…
Prompt Mechanisms in Medical Imaging: A Comprehensive Survey
Hao Yang, Xinlong Liang, Zhang Li +12
Deep learning offers transformative potential in medical imaging, yet its clinical adoption is frequently hampered by challenges such as data scarcity, distribution shifts, and the…
SurfGNN: A robust surface-based prediction model with interpretability for coactivation maps of spatial and cortical features
Zhuoshuo Li, Jiong Zhang, Youbing Zeng +7
Current brain surface-based prediction models often overlook the variability of regional attributes at the cortical feature level. While graph neural networks (GNNs) excel at captu…
CLIP-DR: Textual Knowledge-Guided Diabetic Retinopathy Grading with Ranking-aware Prompting
Qinkai Yu, Jianyang Xie, Anh Nguyen +6
Diabetic retinopathy (DR) is a complication of diabetes and usually takes decades to reach sight-threatening levels. Accurate and robust detection of DR severity is critical for th…
GAPNet: Granularity Attention Network with Anatomy-Prior-Constraint for Carotid Artery Segmentation
Lin Zhang, Chenggang Lu, Xin-yang Shi +4
Atherosclerosis is a chronic, progressive disease that primarily affects the arterial walls. It is one of the major causes of cardiovascular disease. Magnetic Resonance (MR) black-…
DSCA: A Digital Subtraction Angiography Sequence Dataset and Spatio-Temporal Model for Cerebral Artery Segmentation
Jiong Zhang, Qihang Xie, Lei Mou +6
Cerebrovascular diseases (CVDs) remain a leading cause of global disability and mortality. Digital Subtraction Angiography (DSA) sequences, recognized as the gold standard for diag…
Automating Vessel Segmentation in the Heart and Brain: A Trend to Develop Multi-Modality and Label-Efficient Deep Learning Techniques
Nazik Elsayed, Yousuf Babiker M. Osman, Cheng Li +2
Cardio-cerebrovascular diseases are the leading causes of mortality worldwide, whose accurate blood vessel segmentation is significant for both scientific research and clinical usa…
Polar-Net: A Clinical-Friendly Model for Alzheimer's Disease Detection in OCTA Images
Shouyue Liu, Jinkui Hao, Yanwu Xu +7
Optical Coherence Tomography Angiography (OCTA) is a promising tool for detecting Alzheimer's disease (AD) by imaging the retinal microvasculature. Ophthalmologists commonly use re…
Retinal Structure Detection in OCTA Image via Voting-based Multi-task Learning
Jinkui Hao, Ting Shen, Xueli Zhu +7
Automated detection of retinal structures, such as retinal vessels (RV), the foveal avascular zone (FAZ), and retinal vascular junctions (RVJ), are of great importance for understa…
Sparse-based Domain Adaptation Network for OCTA Image Super-Resolution Reconstruction
Huaying Hao, Cong Xu, Dan Zhang +4
Retinal Optical Coherence Tomography Angiography (OCTA) with high-resolution is important for the quantification and analysis of retinal vasculature. However, the resolution of OCT…
3D Vessel Reconstruction in OCT-Angiography via Depth Map Estimation
Shuai Yu, Jianyang Xie, Jinkui Hao +5
Optical Coherence Tomography Angiography (OCTA) has been increasingly used in the management of eye and systemic diseases in recent years. Manual or automatic analysis of blood ves…
ROSE: A Retinal OCT-Angiography Vessel Segmentation Dataset and New Model
Yuhui Ma, Huaying Hao, Huazhu Fu +5
Optical Coherence Tomography Angiography (OCT-A) is a non-invasive imaging technique, and has been increasingly used to image the retinal vasculature at capillary level resolution.…