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20232026
most citedBS-LDM: Effective Bone Suppression in High-Resolution Chest X-Ray Images with Conditional Latent Diffusion Models

6 citations · 12 across the 24 of their papers we have counts for

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11 papers · 1 filter

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.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★ 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

GraphMMP: A Graph Neural Network Model with Mutual Information and Global Fusion for Multimodal Medical Prognosis

Xuhao Shan, Ruiquan Ge, Jikui Liu +7

In the field of multimodal medical data analysis, leveraging diverse types of data and understanding their hidden relationships continues to be a research focus. The main challenge…

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…

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

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…

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…

cs.CV2024

ICHPro: Intracerebral Hemorrhage Prognosis Classification Via Joint-attention Fusion-based 3d Cross-modal Network

Xinlei Yu, Xinyang Li, Ruiquan Ge +8

Intracerebral Hemorrhage (ICH) is the deadliest subtype of stroke, necessitating timely and accurate prognostic evaluation to reduce mortality and disability. However, the multi-fa…