111 citations · 513 across the 24 of their papers we have counts for
24 papers
Inter-slice Super-resolution of Magnetic Resonance Images by Pre-training and Self-supervised Fine-tuning
Xin Wang, Zhiyun Song, Yitao Zhu +4
In clinical practice, 2D magnetic resonance (MR) sequences are widely adopted. While individual 2D slices can be stacked to form a 3D volume, the relatively large slice spacing can…
Gaze-DETR: Using Expert Gaze to Reduce False Positives in Vulvovaginal Candidiasis Screening
Yan Kong, Sheng Wang, Jiangdong Cai +5
Accurate detection of vulvovaginal candidiasis is critical for women's health, yet its sparse distribution and visually ambiguous characteristics pose significant challenges for ac…
MUC: Mixture of Uncalibrated Cameras for Robust 3D Human Body Reconstruction
Yitao Zhu, Sheng Wang, Mengjie Xu +5
Multiple cameras can provide comprehensive multi-view video coverage of a person. Fusing this multi-view data is crucial for tasks like behavioral analysis, although it traditional…
Two-stage Cytopathological Image Synthesis for Augmenting Cervical Abnormality Screening
Zhenrong Shen, Manman Fei, Xin Wang +4
Automatic thin-prep cytologic test (TCT) screening can assist pathologists in finding cervical abnormality towards accurate and efficient cervical cancer diagnosis. Current automat…
Mining Gaze for Contrastive Learning toward Computer-Assisted Diagnosis
Zihao Zhao, Sheng Wang, Qian Wang +1
Obtaining large-scale radiology reports can be difficult for medical images due to various reasons, limiting the effectiveness of contrastive pre-training in the medical image doma…
CLIP in Medical Imaging: A Survey
Zihao Zhao, Yuxiao Liu, Han Wu +8
Contrastive Language-Image Pre-training (CLIP), a simple yet effective pre-training paradigm, successfully introduces text supervision to vision models. It has shown promising resu…
Uni-COAL: A Unified Framework for Cross-Modality Synthesis and Super-Resolution of MR Images
Zhiyun Song, Zengxin Qi, Xin Wang +11
Cross-modality synthesis (CMS), super-resolution (SR), and their combination (CMSR) have been extensively studied for magnetic resonance imaging (MRI). Their primary goals are to e…
MeLo: Low-rank Adaptation is Better than Fine-tuning for Medical Image Diagnosis
Yitao Zhu, Zhenrong Shen, Zihao Zhao +5
The common practice in developing computer-aided diagnosis (CAD) models based on transformer architectures usually involves fine-tuning from ImageNet pre-trained weights. However,…
AdLER: Adversarial Training with Label Error Rectification for One-Shot Medical Image Segmentation
Xiangyu Zhao, Sheng Wang, Zhiyun Song +5
Accurate automatic segmentation of medical images typically requires large datasets with high-quality annotations, making it less applicable in clinical settings due to limited tra…
CellGAN: Conditional Cervical Cell Synthesis for Augmenting Cytopathological Image Classification
Zhenrong Shen, Maosong Cao, Sheng Wang +2
Automatic examination of thin-prep cytologic test (TCT) slides can assist pathologists in finding cervical abnormality for accurate and efficient cancer screening. Current solution…
Learning Better Contrastive View from Radiologist's Gaze
Sheng Wang, Zixu Zhuang, Xi Ouyang +6
Recent self-supervised contrastive learning methods greatly benefit from the Siamese structure that aims to minimizing distances between positive pairs. These methods usually apply…
ChatCAD+: Towards a Universal and Reliable Interactive CAD using LLMs
Zihao Zhao, Sheng Wang, Jinchen Gu +6
The integration of Computer-Aided Diagnosis (CAD) with Large Language Models (LLMs) presents a promising frontier in clinical applications, notably in automating diagnostic process…
DoctorGLM: Fine-tuning your Chinese Doctor is not a Herculean Task
Honglin Xiong, Sheng Wang, Yitao Zhu +5
The recent progress of large language models (LLMs), including ChatGPT and GPT-4, in comprehending and responding to human instructions has been remarkable. Nevertheless, these mod…
Domain Generalization for Mammographic Image Analysis with Contrastive Learning
Zheren Li, Zhiming Cui, Lichi Zhang +10
The deep learning technique has been shown to be effectively addressed several image analysis tasks in the computer-aided diagnosis scheme for mammography. The training of an effic…
Arbitrary Reduction of MRI Inter-slice Spacing Using Hierarchical Feature Conditional Diffusion
Xin Wang, Zhenrong Shen, Zhiyun Song +5
Magnetic resonance (MR) images collected in 2D scanning protocols typically have large inter-slice spacing, resulting in high in-plane resolution but reduced through-plane resoluti…
ChatCAD: Interactive Computer-Aided Diagnosis on Medical Image using Large Language Models
Sheng Wang, Zihao Zhao, Xi Ouyang +2
Large language models (LLMs) have recently demonstrated their potential in clinical applications, providing valuable medical knowledge and advice. For example, a large dialog LLM l…
RCPS: Rectified Contrastive Pseudo Supervision for Semi-Supervised Medical Image Segmentation
Xiangyu Zhao, Zengxin Qi, Sheng Wang +4
Medical image segmentation methods are generally designed as fully-supervised to guarantee model performance, which require a significant amount of expert annotated samples that ar…
TBI-GAN: An Adversarial Learning Approach for Data Synthesis on Traumatic Brain Segmentation
Xiangyu Zhao, Di Zang, Sheng Wang +10
Brain network analysis for traumatic brain injury (TBI) patients is critical for its consciousness level assessment and prognosis evaluation, which requires the segmentation of cer…
Eye-gaze-guided Vision Transformer for Rectifying Shortcut Learning
Chong Ma, Lin Zhao, Yuzhong Chen +15
Learning harmful shortcuts such as spurious correlations and biases prevents deep neural networks from learning the meaningful and useful representations, thus jeopardizing the gen…
Spatial Attention-based Implicit Neural Representation for Arbitrary Reduction of MRI Slice Spacing
Xin Wang, Sheng Wang, Honglin Xiong +7
Magnetic resonance (MR) images collected in 2D clinical protocols typically have large inter-slice spacing, resulting in high in-plane resolution and reduced through-plane resoluti…
Follow My Eye: Using Gaze to Supervise Computer-Aided Diagnosis
Sheng Wang, Xi Ouyang, Tianming Liu +2
When deep neural network (DNN) was first introduced to the medical image analysis community, researchers were impressed by its performance. However, it is evident now that a large…
Knee Cartilage Defect Assessment by Graph Representation and Surface Convolution
Zixu Zhuang, Liping Si, Sheng Wang +8
Knee osteoarthritis (OA) is the most common osteoarthritis and a leading cause of disability. Cartilage defects are regarded as major manifestations of knee OA, which are visible b…
Domain Generalization for Mammography Detection via Multi-style and Multi-view Contrastive Learning
Zheren Li, Zhiming Cui, Sheng Wang +7
Lesion detection is a fundamental problem in the computer-aided diagnosis scheme for mammography. The advance of deep learning techniques have made a remarkable progress for this t…
mr2NST: Multi-Resolution and Multi-Reference Neural Style Transfer for Mammography
Sheng Wang, Jiayu Huo, Xi Ouyang +5
Computer-aided diagnosis with deep learning techniques has been shown to be helpful for the diagnosis of the mammography in many clinical studies. However, the image styles of diff…