316 citations · 2.9k across the 50 of their papers we have counts for
50 papers
Memory-Efficient Prompt Tuning for Incremental Histopathology Classification
Yu Zhu, Kang Li, Lequan Yu +1
Recent studies have made remarkable progress in histopathology classification. Based on current successes, contemporary works proposed to further upgrade the model towards a more g…
Single-Shot Plug-and-Play Methods for Inverse Problems
Yanqi Cheng, Lipei Zhang, Zhenda Shen +5
The utilisation of Plug-and-Play (PnP) priors in inverse problems has become increasingly prominent in recent years. This preference is based on the mathematical equivalence betwee…
HIGT: Hierarchical Interaction Graph-Transformer for Whole Slide Image Analysis
Ziyu Guo, Weiqin Zhao, Shujun Wang +1
In computation pathology, the pyramid structure of gigapixel Whole Slide Images (WSIs) has recently been studied for capturing various information from individual cell interactions…
Cheap Lunch for Medical Image Segmentation by Fine-tuning SAM on Few Exemplars
Weijia Feng, Lingting Zhu, Lequan Yu
The Segment Anything Model (SAM) has demonstrated remarkable capabilities of scaled-up segmentation models, enabling zero-shot generalization across a variety of domains. By levera…
ConSlide: Asynchronous Hierarchical Interaction Transformer with Breakup-Reorganize Rehearsal for Continual Whole Slide Image Analysis
Yanyan Huang, Weiqin Zhao, Shujun Wang +3
Whole slide image (WSI) analysis has become increasingly important in the medical imaging community, enabling automated and objective diagnosis, prognosis, and therapeutic-response…
Make-A-Volume: Leveraging Latent Diffusion Models for Cross-Modality 3D Brain MRI Synthesis
Lingting Zhu, Zeyue Xue, Zhenchao Jin +4
Cross-modality medical image synthesis is a critical topic and has the potential to facilitate numerous applications in the medical imaging field. Despite recent successes in deep-…
Histopathology Whole Slide Image Analysis with Heterogeneous Graph Representation Learning
Tsai Hor Chan, Fernando Julio Cendra, Lan Ma +2
Graph-based methods have been extensively applied to whole-slide histopathology image (WSI) analysis due to the advantage of modeling the spatial relationships among different enti…
MulGT: Multi-task Graph-Transformer with Task-aware Knowledge Injection and Domain Knowledge-driven Pooling for Whole Slide Image Analysis
Weiqin Zhao, Shujun Wang, Maximus Yeung +2
Whole slide image (WSI) has been widely used to assist automated diagnosis under the deep learning fields. However, most previous works only discuss the SINGLE task setting which i…
HybridMIM: A Hybrid Masked Image Modeling Framework for 3D Medical Image Segmentation
Zhaohu Xing, Lei Zhu, Lequan Yu +2
Masked image modeling (MIM) with transformer backbones has recently been exploited as a powerful self-supervised pre-training technique. The existing MIM methods adopt the strategy…
Taming Diffusion Models for Audio-Driven Co-Speech Gesture Generation
Lingting Zhu, Xian Liu, Xuanyu Liu +3
Animating virtual avatars to make co-speech gestures facilitates various applications in human-machine interaction. The existing methods mainly rely on generative adversarial netwo…
MagicNet: Semi-Supervised Multi-Organ Segmentation via Magic-Cube Partition and Recovery
Duowen Chen, Yunhao Bai, Wei Shen +3
We propose a novel teacher-student model for semi-supervised multi-organ segmentation. In teacher-student model, data augmentation is usually adopted on unlabeled data to regulariz…
Domain-incremental Cardiac Image Segmentation with Style-oriented Replay and Domain-sensitive Feature Whitening
Kang Li, Lequan Yu, Pheng-Ann Heng
Contemporary methods have shown promising results on cardiac image segmentation, but merely in static learning, i.e., optimizing the network once for all, ignoring potential needs…
Multi-Granularity Cross-modal Alignment for Generalized Medical Visual Representation Learning
Fuying Wang, Yuyin Zhou, Shujun Wang +2
Learning medical visual representations directly from paired radiology reports has become an emerging topic in representation learning. However, existing medical image-text joint l…
MCIBI++: Soft Mining Contextual Information Beyond Image for Semantic Segmentation
Zhenchao Jin, Dongdong Yu, Zehuan Yuan +1
Co-occurrent visual pattern makes context aggregation become an essential paradigm for semantic segmentation.The existing studies focus on modeling the contexts within image while…
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…
NestedFormer: Nested Modality-Aware Transformer for Brain Tumor Segmentation
Zhaohu Xing, Lequan Yu, Liang Wan +2
Multi-modal MR imaging is routinely used in clinical practice to diagnose and investigate brain tumors by providing rich complementary information. Previous multi-modal MRI segment…
Robust Medical Image Classification from Noisy Labeled Data with Global and Local Representation Guided Co-training
Cheng Xue, Lequan Yu, Pengfei Chen +2
Deep neural networks have achieved remarkable success in a wide variety of natural image and medical image computing tasks. However, these achievements indispensably rely on accura…
nnFormer: Interleaved Transformer for Volumetric Segmentation
Hong-Yu Zhou, Jiansen Guo, Yinghao Zhang +3
Transformer, the model of choice for natural language processing, has drawn scant attention from the medical imaging community. Given the ability to exploit long-term dependencies,…
Dual-Teacher++: Exploiting Intra-domain and Inter-domain Knowledge with Reliable Transfer for Cardiac Segmentation
Kang Li, Shujun Wang, Lequan Yu +1
Annotation scarcity is a long-standing problem in medical image analysis area. To efficiently leverage limited annotations, abundant unlabeled data are additionally exploited in se…
RMDL: Recalibrated multi-instance deep learning for whole slide gastric image classification
Shujun Wang, Yaxi Zhu, Lequan Yu +5
The whole slide histopathology images (WSIs) play a critical role in gastric cancer diagnosis. However, due to the large scale of WSIs and various sizes of the abnormal area, how t…
DoFE: Domain-oriented Feature Embedding for Generalizable Fundus Image Segmentation on Unseen Datasets
Shujun Wang, Lequan Yu, Kang Li +3
Deep convolutional neural networks have significantly boosted the performance of fundus image segmentation when test datasets have the same distribution as the training datasets. H…
Towards Cross-modality Medical Image Segmentation with Online Mutual Knowledge Distillation
Kang Li, Lequan Yu, Shujun Wang +1
The success of deep convolutional neural networks is partially attributed to the massive amount of annotated training data. However, in practice, medical data annotations are usual…
Deep Sinogram Completion with Image Prior for Metal Artifact Reduction in CT Images
Lequan Yu, Zhicheng Zhang, Xiaomeng Li +1
Computed tomography (CT) has been widely used for medical diagnosis, assessment, and therapy planning and guidance. In reality, CT images may be affected adversely in the presence…
Self-supervised Feature Learning via Exploiting Multi-modal Data for Retinal Disease Diagnosis
Xiaomeng Li, Mengyu Jia, Md Tauhidul Islam +2
The automatic diagnosis of various retinal diseases from fundus images is important to support clinical decision-making. However, developing such automatic solutions is challenging…