42 citations · 121 across the 17 of their papers we have counts for
17 papers
DomainVerse: A Benchmark Towards Real-World Distribution Shifts For Tuning-Free Adaptive Domain Generalization
Feng Hou, Jin Yuan, Ying Yang +7
Traditional cross-domain tasks, including domain adaptation and domain generalization, rely heavily on training model by source domain data. With the recent advance of vision-langu…
Epistemic Graph: A Plug-And-Play Module For Hybrid Representation Learning
Jin Yuan, Yang Zhang, Yangzhou Du +4
In recent years, deep models have achieved remarkable success in various vision tasks. However, their performance heavily relies on large training datasets. In contrast, humans exh…
Learning to Learn Domain-invariant Parameters for Domain Generalization
Feng Hou, Yao Zhang, Yang Liu +6
Due to domain shift, deep neural networks (DNNs) usually fail to generalize well on unknown test data in practice. Domain generalization (DG) aims to overcome this issue by capturi…
SAP-DETR: Bridging the Gap Between Salient Points and Queries-Based Transformer Detector for Fast Model Convergency
Yang Liu, Yao Zhang, Yixin Wang +5
Recently, the dominant DETR-based approaches apply central-concept spatial prior to accelerate Transformer detector convergency. These methods gradually refine the reference points…
mmFormer: Multimodal Medical Transformer for Incomplete Multimodal Learning of Brain Tumor Segmentation
Yao Zhang, Nanjun He, Jiawei Yang +6
Accurate brain tumor segmentation from Magnetic Resonance Imaging (MRI) is desirable to joint learning of multimodal images. However, in clinical practice, it is not always possibl…
Decoupled Pyramid Correlation Network for Liver Tumor Segmentation from CT images
Yao Zhang, Jiawei Yang, Yang Liu +6
Purpose: Automated liver tumor segmentation from Computed Tomography (CT) images is a necessary prerequisite in the interventions of hepatic abnormalities and surgery planning. How…
Analyzing the Effects of Handling Data Imbalance on Learned Features from Medical Images by Looking Into the Models
Ashkan Khakzar, Yawei Li, Yang Zhang +5
One challenging property lurking in medical datasets is the imbalanced data distribution, where the frequency of the samples between the different classes is not balanced. Training…
A Survey of Visual Transformers
Yang Liu, Yao Zhang, Yixin Wang +7
Transformer, an attention-based encoder-decoder model, has already revolutionized the field of natural language processing (NLP). Inspired by such significant achievements, some pi…
Learning Rich Features for Gait Recognition by Integrating Skeletons and Silhouettes
Yunjie Peng, Kang Ma, Yang Zhang +1
Gait recognition captures gait patterns from the walking sequence of an individual for identification. Most existing gait recognition methods learn features from silhouettes or ske…
TumorCP: A Simple but Effective Object-Level Data Augmentation for Tumor Segmentation
Jiawei Yang, Yao Zhang, Yuan Liang +3
Deep learning models are notoriously data-hungry. Thus, there is an urging need for data-efficient techniques in medical image analysis, where well-annotated data are costly and ti…
Modality-aware Mutual Learning for Multi-modal Medical Image Segmentation
Yao Zhang, Jiawei Yang, Jiang Tian +4
Liver cancer is one of the most common cancers worldwide. Due to inconspicuous texture changes of liver tumor, contrast-enhanced computed tomography (CT) imaging is effective for t…
ACN: Adversarial Co-training Network for Brain Tumor Segmentation with Missing Modalities
Yixin Wang, Yang Zhang, Yang Liu +6
Accurate segmentation of brain tumors from magnetic resonance imaging (MRI) is clinically relevant in diagnoses, prognoses and surgery treatment, which requires multiple modalities…
Trust It or Not: Confidence-Guided Automatic Radiology Report Generation
Yixin Wang, Zihao Lin, Zhe Xu +7
Medical imaging plays a pivotal role in diagnosis and treatment in clinical practice. Inspired by the significant progress in automatic image captioning, various deep learning (DL)…
Semi-supervised Cardiac Image Segmentation via Label Propagation and Style Transfer
Yao Zhang, Jiawei Yang, Feng Hou +6
Accurate segmentation of cardiac structures can assist doctors to diagnose diseases, and to improve treatment planning, which is highly demanded in the clinical practice. However,…
Double-Uncertainty Weighted Method for Semi-supervised Learning
Yixin Wang, Yao Zhang, Jiang Tian +4
Though deep learning has achieved advanced performance recently, it remains a challenging task in the field of medical imaging, as obtaining reliable labeled training data is time-…
Modality-Pairing Learning for Brain Tumor Segmentation
Yixin Wang, Yao Zhang, Feng Hou +5
Automatic brain tumor segmentation from multi-modality Magnetic Resonance Images (MRI) using deep learning methods plays an important role in assisting the diagnosis and treatment…
Semantic Feature Attention Network for Liver Tumor Segmentation in Large-scale CT database
Yao Zhang, Cheng Zhong, Yang Zhang +2
Liver tumor segmentation plays an important role in hepatocellular carcinoma diagnosis and surgical planning. In this paper, we propose a novel Semantic Feature Attention Network (…