6 citations · 8 across the 19 of their papers we have counts for
19 papers
USCNet: Transformer-Based Multimodal Fusion with Segmentation Guidance for Urolithiasis Classification
Changmiao Wang, Songqi Zhang, Yongquan Zhang +9
Kidney stone disease ranks among the most prevalent conditions in urology, and understanding the composition of these stones is essential for creating personalized treatment plans…
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…
Balancing Efficiency and Restoration: Lightweight Mamba-Based Model for CT Metal Artifact Reduction
Weikai Qu, Sijun Liang, Xianfeng Li +7
In computed tomography imaging, metal implants frequently generate severe artifacts that compromise image quality and hinder diagnostic accuracy. There are three main challenges in…
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…
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…
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…
CRISP-SAM2: SAM2 with Cross-Modal Interaction and Semantic Prompting for Multi-Organ Segmentation
Xinlei Yu, Changmiao Wang, Hui Jin +5
Multi-organ medical segmentation is a crucial component of medical image processing, essential for doctors to make accurate diagnoses and develop effective treatment plans. Despite…
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…
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…
ITCFN: Incomplete Triple-Modal Co-Attention Fusion Network for Mild Cognitive Impairment Conversion Prediction
Xiangyang Hu, Xiangyu Shen, Yifei Sun +8
Alzheimer's disease (AD) is a common neurodegenerative disease among the elderly. Early prediction and timely intervention of its prodromal stage, mild cognitive impairment (MCI),…
BS-LDM: Effective Bone Suppression in High-Resolution Chest X-Ray Images with Conditional Latent Diffusion Models
Yifei Sun, Zhanghao Chen, Hao Zheng +7
Lung diseases represent a significant global health challenge, with Chest X-Ray (CXR) being a key diagnostic tool due to its accessibility and affordability. Nonetheless, the detec…
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…
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…
UWAFA-GAN: Ultra-Wide-Angle Fluorescein Angiography Transformation via Multi-scale Generation and Registration Enhancement
Ruiquan Ge, Zhaojie Fang, Pengxue Wei +7
Fundus photography, in combination with the ultra-wide-angle fundus (UWF) techniques, becomes an indispensable diagnostic tool in clinical settings by offering a more comprehensive…
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…
GCS-ICHNet: Assessment of Intracerebral Hemorrhage Prognosis using Self-Attention with Domain Knowledge Integration
Xuhao Shan, Xinyang Li, Ruiquan Ge +8
Intracerebral Hemorrhage (ICH) is a severe condition resulting from damaged brain blood vessel ruptures, often leading to complications and fatalities. Timely and accurate prognosi…
BS-Diff: Effective Bone Suppression Using Conditional Diffusion Models from Chest X-Ray Images
Zhanghao Chen, Yifei Sun, Wenjian Qin +8
Chest X-rays (CXRs) are commonly utilized as a low-dose modality for lung screening. Nonetheless, the efficacy of CXRs is somewhat impeded, given that approximately 75% of the lung…