111 citations · 513 across the 24 of their papers we have counts for
13 papers · 1 filter
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…