activity
20232026
most citedAccurate Leukocyte Detection Based on Deformable-DETR and Multi-Level Feature Fusion for Aiding Diagnosis of Blood Diseases

9 citations · 26 across the 36 of their papers we have counts for

collaborators

40 papers

cs.CV2026

DeBoneDiT: Depth-Driven Conditional Bridge Diffusion Transformers for Bone Suppression in Chest X-Ray Images

Yifei Sun, Fenglei Fan, Junhao Jia +4

Chest X-Ray (CXR) is a primary modality for diagnosing pulmonary diseases, yet the overlap of bony structures often obscures critical radiographic findings, increasing the risk of…

cs.CV2026

R2AoP: Reliable and Robust Angle of Progression Estimation from Intrapartum Ultrasound

Yuanhan Wang, Yifei Chen, Beining Wu +7

Accurate estimation of the Angle of Progression (AoP) from intrapartum transperineal ultrasound is critical for objective assessment of labor progression, yet remains highly sensit…

cs.CV2026★ 1 cited

WeatherRemover: All-in-one Adverse Weather Removal with Multi-scale Feature Map Compression

Weikai Qu, Sijun Liang, Cheng Pan +6

Photographs taken in adverse weather conditions often suffer from blurriness, occlusion, and low brightness due to interference from rain, snow, and fog. These issues can significa…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025★ 1 cited

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025★ 2 cited

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

eess.IV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

eess.IV2025

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…

eess.IV2024

XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision XLSTM and Heteromodal Variational Encoder-Decoder

Shenghao Zhu, Yifei Chen, Shuo Jiang +8

Neurogliomas are among the most aggressive forms of cancer, presenting considerable challenges in both treatment and monitoring due to their unpredictable biological behavior. Magn…

cs.CV2024

ICH-SCNet: Intracerebral Hemorrhage Segmentation and Prognosis Classification Network Using CLIP-guided SAM mechanism

Xinlei Yu, Ahmed Elazab, Ruiquan Ge +6

Intracerebral hemorrhage (ICH) is the most fatal subtype of stroke and is characterized by a high incidence of disability. Accurate segmentation of the ICH region and prognosis pre…

cs.CV2024

LPUWF-LDM: Enhanced Latent Diffusion Model for Precise Late-phase UWF-FA Generation on Limited Dataset

Zhaojie Fang, Xiao Yu, Guanyu Zhou +10

Ultra-Wide-Field Fluorescein Angiography (UWF-FA) enables precise identification of ocular diseases using sodium fluorescein, which can be potentially harmful. Existing research ha…