9 citations · 26 across the 36 of their papers we have counts for
18 papers · 1 filter
DGSAN: Dual-Graph Spatiotemporal Attention Network for Pulmonary Nodule Malignancy Prediction
Xiao Yu, Zhaojie Fang, Guanyu Zhou +7
Lung cancer continues to be the leading cause of cancer-related deaths globally. Early detection and diagnosis of pulmonary nodules are essential for improving patient survival rat…
WDT-MD: Wavelet Diffusion Transformers for Microaneurysm Detection in Fundus Images
Yifei Sun, Yuzhi He, Junhao Jia +4
Microaneurysms (MAs), the earliest pathognomonic signs of Diabetic Retinopathy (DR), present as sub-60 lesions in fundus images with highly variable photometric and morphologi…
A Large Scale Benchmark for Test Time Adaptation Methods in Medical Image Segmentation
Wenjing Yu, Shuo Jiang, Yifei Chen +9
Test time Adaptation is a promising approach for mitigating domain shift in medical image segmentation; however, current evaluations remain limited in terms of modality coverage, t…
LungNoduleAgent: A Collaborative Multi-Agent System for Precision Diagnosis of Lung Nodules
Cheng Yang, Hui Jin, Xinlei Yu +7
Diagnosing lung cancer typically involves physicians identifying lung nodules in Computed tomography (CT) scans and generating diagnostic reports based on their morphological featu…
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…
SmaRT: Style-Modulated Robust Test-Time Adaptation for Cross-Domain Brain Tumor Segmentation in MRI
Yuanhan Wang, Yifei Chen, Shuo Jiang +7
Reliable brain tumor segmentation in MRI is indispensable for treatment planning and outcome monitoring, yet models trained on curated benchmarks often fail under domain shifts ari…
Drawing2CAD: Sequence-to-Sequence Learning for CAD Generation from Vector Drawings
Feiwei Qin, Shichao Lu, Junhao Hou +3
Computer-Aided Design (CAD) generative modeling is driving significant innovations across industrial applications. Recent works have shown remarkable progress in creating solid mod…
Geodesic Prototype Matching via Diffusion Maps for Interpretable Fine-Grained Recognition
Junhao Jia, Yunyou Liu, Yifei Sun +4
Nonlinear manifolds are pervasive in deep visual features, where Euclidean distances can misrepresent true similarity. This mismatch is particularly detrimental to prototype-based…
No Modality Left Behind: Adapting to Missing Modalities via Knowledge Distillation for Brain Tumor Segmentation
Shenghao Zhu, Yifei Chen, Weihong Chen +6
Accurate brain tumor segmentation is essential for preoperative evaluation and personalized treatment. Multi-modal MRI is widely used due to its ability to capture complementary tu…
Brain-HGCN: A Hyperbolic Graph Convolutional Network for Brain Functional Network Analysis
Junhao Jia, Yunyou Liu, Cheng Yang +4
Functional magnetic resonance imaging (fMRI) reveals complex brain functional networks with hierarchical topologies crucial for cognitive processing. Standard Euclidean Graph Neura…
RTGMFF: Enhanced fMRI-based Brain Disorder Diagnosis via ROI-driven Text Generation and Multimodal Feature Fusion
Junhao Jia, Yifei Sun, Yunyou Liu +5
Functional magnetic resonance imaging (fMRI) is a powerful tool for probing brain function, yet reliable clinical diagnosis is hampered by low signal-to-noise ratios, inter-subject…
Small Lesions-aware Bidirectional Multimodal Multiscale Fusion Network for Lung Disease Classification
Jianxun Yu, Ruiquan Ge, Zhipeng Wang +6
The diagnosis of medical diseases faces challenges such as the misdiagnosis of small lesions. Deep learning, particularly multimodal approaches, has shown great potential in the fi…
GL-LCM: Global-Local Latent Consistency Models for Fast High-Resolution Bone Suppression in Chest X-Ray Images
Yifei Sun, Zhanghao Chen, Hao Zheng +7
Chest X-Ray (CXR) imaging for pulmonary diagnosis raises significant challenges, primarily because bone structures can obscure critical details necessary for accurate diagnosis. Re…
Bridging the Gap in Missing Modalities: Leveraging Knowledge Distillation and Style Matching for Brain Tumor Segmentation
Shenghao Zhu, Yifei Chen, Weihong Chen +5
Accurate and reliable brain tumor segmentation, particularly when dealing with missing modalities, remains a critical challenge in medical image analysis. Previous studies have not…
3D-Telepathy: Reconstructing 3D Objects from EEG Signals
Yuxiang Ge, Jionghao Cheng, Ruiquan Ge +6
Reconstructing 3D visual stimuli from Electroencephalography (EEG) data holds significant potential for applications in Brain-Computer Interfaces (BCIs) and aiding individuals with…
Towards Practical Alzheimer's Disease Diagnosis: A Lightweight and Interpretable Spiking Neural Model
Changwei Wu, Yifei Chen, Yuxin Du +7
Early diagnosis of Alzheimer's Disease (AD), particularly at the mild cognitive impairment stage, is essential for timely intervention. However, this process faces significant barr…
TMI-CLNet: Triple-Modal Interaction Network for Chronic Liver Disease Prognosis From Imaging, Clinical, and Radiomic Data Fusion
Linglong Wu, Xuhao Shan, Ruiquan Ge +7
Chronic liver disease represents a significant health challenge worldwide and accurate prognostic evaluations are essential for personalized treatment plans. Recent evidence sugges…
CSF-Net: Cross-Modal Spatiotemporal Fusion Network for Pulmonary Nodule Malignancy Predicting
Yin Shen, Zhaojie Fang, Ke Zhuang +8
Pulmonary nodules are an early sign of lung cancer, and detecting them early is vital for improving patient survival rates. Most current methods use only single Computed Tomography…