2.3k citations · 7.6k across the 114 of their papers we have counts for
26 papers · 1 filter
Specificity-Preserving Federated Learning for MR Image Reconstruction
Chun-Mei Feng, Yunlu Yan, Shanshan Wang +3
Federated learning (FL) can be used to improve data privacy and efficiency in magnetic resonance (MR) image reconstruction by enabling multiple institutions to collaborate without…
Trustworthy Multimodal Regression with Mixture of Normal-inverse Gamma Distributions
Huan Ma, Zongbo Han, Changqing Zhang +3
Multimodal regression is a fundamental task, which integrates the information from different sources to improve the performance of follow-up applications. However, existing methods…
Trustworthy Long-Tailed Classification
Bolian Li, Zongbo Han, Haining Li +2
Classification on long-tailed distributed data is a challenging problem, which suffers from serious class-imbalance and accordingly unpromising performance especially on tail class…
Proxy-bridged Image Reconstruction Network for Anomaly Detection in Medical Images
Kang Zhou, Jing Li, Weixin Luo +6
Anomaly detection in medical images refers to the identification of abnormal images with only normal images in the training set. Most existing methods solve this problem with a sel…
Deep multi-modal aggregation network for MR image reconstruction with auxiliary modality
Chun-Mei Feng, Huazhu Fu, Tianfei Zhou +3
Magnetic resonance (MR) imaging produces detailed images of organs and tissues with better contrast, but it suffers from a long acquisition time, which makes the image quality vuln…
Exploring Separable Attention for Multi-Contrast MR Image Super-Resolution
Chun-Mei Feng, Yunlu Yan, Kai Yu +3
Super-resolving the Magnetic Resonance (MR) image of a target contrast under the guidance of the corresponding auxiliary contrast, which provides additional anatomical information,…
VIL-100: A New Dataset and A Baseline Model for Video Instance Lane Detection
Yujun Zhang, Lei Zhu, Wei Feng +5
Lane detection plays a key role in autonomous driving. While car cameras always take streaming videos on the way, current lane detection works mainly focus on individual images (fr…
From Synthetic to Real: Image Dehazing Collaborating with Unlabeled Real Data
Ye Liu, Lei Zhu, Shunda Pei +5
Single image dehazing is a challenging task, for which the domain shift between synthetic training data and real-world testing images usually leads to degradation of existing metho…
Specificity-preserving RGB-D Saliency Detection
Tao Zhou, Deng-Ping Fan, Geng Chen +2
Salient object detection (SOD) on RGB and depth images has attracted more and more research interests, due to its effectiveness and the fact that depth cues can now be conveniently…
Polyp-PVT: Polyp Segmentation with Pyramid Vision Transformers
Bo Dong, Wenhai Wang, Deng-Ping Fan +3
Most polyp segmentation methods use CNNs as their backbone, leading to two key issues when exchanging information between the encoder and decoder: 1) taking into account the differ…
Few-Shot Domain Adaptation with Polymorphic Transformers
Shaohua Li, Xiuchao Sui, Jie Fu +7
Deep neural networks (DNNs) trained on one set of medical images often experience severe performance drop on unseen test images, due to various domain discrepancy between the train…
DONet: Dual-Octave Network for Fast MR Image Reconstruction
Chun-Mei Feng, Zhanyuan Yang, Huazhu Fu +3
Magnetic resonance (MR) image acquisition is an inherently prolonged process, whose acceleration has long been the subject of research. This is commonly achieved by obtaining multi…
Multi-Modal Transformer for Accelerated MR Imaging
Chun-Mei Feng, Yunlu Yan, Geng Chen +3
Accelerated multi-modal magnetic resonance (MR) imaging is a new and effective solution for fast MR imaging, providing superior performance in restoring the target modality from it…
Federated Noisy Client Learning
Kahou Tam, Li Li, Bo Han +2
Federated learning (FL) collaboratively trains a shared global model depending on multiple local clients, while keeping the training data decentralized in order to preserve data pr…
Task Transformer Network for Joint MRI Reconstruction and Super-Resolution
Chun-Mei Feng, Yunlu Yan, Huazhu Fu +2
The core problem of Magnetic Resonance Imaging (MRI) is the trade off between acceleration and image quality. Image reconstruction and super-resolution are two crucial techniques i…
Progressively Normalized Self-Attention Network for Video Polyp Segmentation
Ge-Peng Ji, Yu-Cheng Chou, Deng-Ping Fan +4
Existing video polyp segmentation (VPS) models typically employ convolutional neural networks (CNNs) to extract features. However, due to their limited receptive fields, CNNs can n…
A Multi-Branch Hybrid Transformer Networkfor Corneal Endothelial Cell Segmentation
Yinglin Zhang, Risa Higashita, Huazhu Fu +5
Corneal endothelial cell segmentation plays a vital role inquantifying clinical indicators such as cell density, coefficient of variation,and hexagonality. However, the corneal end…
Combating Ambiguity for Hash-code Learning in Medical Instance Retrieval
Jiansheng Fang, Huazhu Fu, Dan Zeng +3
When encountering a dubious diagnostic case, medical instance retrieval can help radiologists make evidence-based diagnoses by finding images containing instances similar to a quer…
Group Collaborative Learning for Co-Salient Object Detection
Qi Fan, Deng-Ping Fan, Huazhu Fu +3
We present a novel group collaborative learning framework (GCoNet) capable of detecting co-salient objects in real time (16ms), by simultaneously mining consensus representations a…
Multi-Contrast MRI Super-Resolution via a Multi-Stage Integration Network
Chun-Mei Feng, Huazhu Fu, Shuhao Yuan +1
Super-resolution (SR) plays a crucial role in improving the image quality of magnetic resonance imaging (MRI). MRI produces multi-contrast images and can provide a clear display of…
VideoLT: Large-scale Long-tailed Video Recognition
Xing Zhang, Zuxuan Wu, Zejia Weng +4
Label distributions in real-world are oftentimes long-tailed and imbalanced, resulting in biased models towards dominant labels. While long-tailed recognition has been extensively…
Global Guidance Network for Breast Lesion Segmentation in Ultrasound Images
Cheng Xue, Lei Zhu, Huazhu Fu +4
Automatic breast lesion segmentation in ultrasound helps to diagnose breast cancer, which is one of the dreadful diseases that affect women globally. Segmenting breast regions accu…
Triple-cooperative Video Shadow Detection
Zhihao Chen, Liang Wan, Lei Zhu +4
Shadow detection in a single image has received significant research interest in recent years. However, much fewer works have been explored in shadow detection over dynamic scenes.…
Trusted Multi-View Classification
Zongbo Han, Changqing Zhang, Huazhu Fu +1
Multi-view classification (MVC) generally focuses on improving classification accuracy by using information from different views, typically integrating them into a unified comprehe…