343 citations · 980 across the 21 of their papers we have counts for
22 papers
Clump-scale Gas Infall in High-mass Star Formation: a Multi-transition View with JCMT HCN (4--3) Mapping
Fengwei Xu, Ke Wang, Yuxin He +3
Gas infall motions play a crucial role in high-mass star formation and are characterized by observable signatures in the form of blue-shifted asymmetric spectral line profiles ("bl…
Video Adverse-Weather-Component Suppression Network via Weather Messenger and Adversarial Backpropagation
Yijun Yang, Angelica I. Aviles-Rivero, Huazhu Fu +3
Although convolutional neural networks (CNNs) have been proposed to remove adverse weather conditions in single images using a single set of pre-trained weights, they fail to resto…
Federated Pseudo Modality Generation for Incomplete Multi-Modal MRI Reconstruction
Yunlu Yan, Chun-Mei Feng, Yuexiang Li +2
While multi-modal learning has been widely used for MRI reconstruction, it relies on paired multi-modal data which is difficult to acquire in real clinical scenarios. Especially in…
Cross-Modal Retrieval: A Systematic Review of Methods and Future Directions
Tianshi Wang, Fengling Li, Lei Zhu +3
With the exponential surge in diverse multi-modal data, traditional uni-modal retrieval methods struggle to meet the needs of users seeking access to data across various modalities…
Dynamic Interactive Relation Capturing via Scene Graph Learning for Robotic Surgical Report Generation
Hongqiu Wang, Yueming Jin, Lei Zhu
For robot-assisted surgery, an accurate surgical report reflects clinical operations during surgery and helps document entry tasks, post-operative analysis and follow-up treatment.…
A Simple Data Augmentation for Feature Distribution Skewed Federated Learning
Yunlu Yan, Huazhu Fu, Yuexiang Li +4
Federated Learning (FL) facilitates collaborative learning among multiple clients in a distributed manner and ensures the security of privacy. However, its performance inevitably d…
Benchmarking Large Language Models on CMExam -- A Comprehensive Chinese Medical Exam Dataset
Junling Liu, Peilin Zhou, Yining Hua +8
Recent advancements in large language models (LLMs) have transformed the field of question answering (QA). However, evaluating LLMs in the medical field is challenging due to the l…
Diff-UNet: A Diffusion Embedded Network for Volumetric Segmentation
Zhaohu Xing, Liang Wan, Huazhu Fu +2
In recent years, Denoising Diffusion Models have demonstrated remarkable success in generating semantically valuable pixel-wise representations for image generative modeling. In th…
Video Dehazing via a Multi-Range Temporal Alignment Network with Physical Prior
Jiaqi Xu, Xiaowei Hu, Lei Zhu +4
Video dehazing aims to recover haze-free frames with high visibility and contrast. This paper presents a novel framework to effectively explore the physical haze priors and aggrega…
Learning Physical-Spatio-Temporal Features for Video Shadow Removal
Zhihao Chen, Liang Wan, Yefan Xiao +2
Shadow removal in a single image has received increasing attention in recent years. However, removing shadows over dynamic scenes remains largely under-explored. In this paper, we…
DiffMIC: Dual-Guidance Diffusion Network for Medical Image Classification
Yijun Yang, Huazhu Fu, Angelica I. Aviles-Rivero +2
Diffusion Probabilistic Models have recently shown remarkable performance in generative image modeling, attracting significant attention in the computer vision community. However,…
A Comprehensive Survey on Source-free Domain Adaptation
Zhiqi Yu, Jingjing Li, Zhekai Du +2
Over the past decade, domain adaptation has become a widely studied branch of transfer learning that aims to improve performance on target domains by leveraging knowledge from the…
Joint Prediction of Meningioma Grade and Brain Invasion via Task-Aware Contrastive Learning
Tianling Liu, Wennan Liu, Lequan Yu +3
Preoperative and noninvasive prediction of the meningioma grade is important in clinical practice, as it directly influences the clinical decision making. What's more, brain invasi…
A New Dataset and A Baseline Model for Breast Lesion Detection in Ultrasound Videos
Zhi Lin, Junhao Lin, Lei Zhu +3
Breast lesion detection in ultrasound is critical for breast cancer diagnosis. Existing methods mainly rely on individual 2D ultrasound images or combine unlabeled video and labele…
Multi-modal learning for predicting the genotype of glioma
Yiran Wei, Xi Chen, Lei Zhu +4
The isocitrate dehydrogenase (IDH) gene mutation is an essential biomarker for the diagnosis and prognosis of glioma. It is promising to better predict glioma genotype by integrati…
Maximum Density Divergence for Domain Adaptation
Li Jingjing, Chen Erpeng, Ding Zhengming +3
Unsupervised domain adaptation addresses the problem of transferring knowledge from a well-labeled source domain to an unlabeled target domain where the two domains have distinctiv…
CANet: Cross-disease Attention Network for Joint Diabetic Retinopathy and Diabetic Macular Edema Grading
Xiaomeng Li, Xiaowei Hu, Lequan Yu +3
Diabetic retinopathy (DR) and diabetic macular edema (DME) are the leading causes of permanent blindness in the working-age population. Automatic grading of DR and DME helps ophtha…
Probabilistic Multilayer Regularization Network for Unsupervised 3D Brain Image Registration
Lihao Liu, Xiaowei Hu, Lei Zhu +1
Brain image registration transforms a pair of images into one system with the matched imaging contents, which is of essential importance for brain image analysis. This paper presen…
Deep Attentive Features for Prostate Segmentation in 3D Transrectal Ultrasound
Yi Wang, Haoran Dou, Xiaowei Hu +7
Automatic prostate segmentation in transrectal ultrasound (TRUS) images is of essential importance for image-guided prostate interventions and treatment planning. However, developi…
Locality Preserving Joint Transfer for Domain Adaptation
Li Jingjing, Jing Mengmeng, Lu Ke +2
Domain adaptation aims to leverage knowledge from a well-labeled source domain to a poorly-labeled target domain. A majority of existing works transfer the knowledge at either feat…
SAC-Net: Spatial Attenuation Context for Salient Object Detection
Xiaowei Hu, Chi-Wing Fu, Lei Zhu +2
This paper presents a new deep neural network design for salient object detection by maximizing the integration of local and global image context within, around, and beyond the sal…
Direction-aware Spatial Context Features for Shadow Detection and Removal
Xiaowei Hu, Chi-Wing Fu, Lei Zhu +2
Shadow detection and shadow removal are fundamental and challenging tasks, requiring an understanding of the global image semantics. This paper presents a novel deep neural network…