2 citations · 3 across the 9 of their papers we have counts for
9 papers
Multi-Contrast MRI Motion Correction via Parameter-Informed Disentanglement and Adaptive Experts
Honglin Xiong, Yuxian Tang, Feng Li +4
Motion artifacts in magnetic resonance imaging (MRI) degrade diagnostic reliability. Existing deep learning methods are typically contrast-specific and fail to generalize across di…
VisionCAD: An Integration-Free Radiology Copilot Framework
Jiaming Li, Junlei Wu, Sheng Wang +7
Widespread clinical deployment of computer-aided diagnosis (CAD) systems is hindered by the challenge of integrating with existing hospital IT infrastructure. Here, we introduce Vi…
Brain Connectivity Network Structure Learning For Brain Disorder Diagnosis
Dongdong Chen, Linlin Yao, Mengjun Liu +7
Recent studies in neuroscience highlight the significant potential of brain connectivity networks, which are commonly constructed from functional magnetic resonance imaging (fMRI)…
UniCAD: Efficient and Extendable Architecture for Multi-Task Computer-Aided Diagnosis System
Yitao Zhu, Yuan Yin, Zhenrong Shen +5
The growing complexity and scale of visual model pre-training have made developing and deploying multi-task computer-aided diagnosis (CAD) systems increasingly challenging and reso…
Towards General Text-guided Image Synthesis for Customized Multimodal Brain MRI Generation
Yulin Wang, Honglin Xiong, Kaicong Sun +7
Multimodal brain magnetic resonance (MR) imaging is indispensable in neuroscience and neurology. However, due to the accessibility of MRI scanners and their lengthy acquisition tim…
Evaluating the evolution and inter-individual variability of infant functional module development from 0 to 5 years old
Lingbin Bian, Nizhuan Wang, Yuanning Li +5
The segregation and integration of infant brain networks undergo tremendous changes due to the rapid development of brain function and organization. Traditional methods for estimat…
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…
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…
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,…