Publications (6)
MedARC: Training-Free Adaptive Redundancy Compression of Visual Tokens for 3D Medical Vision-Language Models
Yitao Zhu, Mengjun Liu, Yingji Fu +2
MedARC is a training-free method that compresses redundant visual tokens in 3D medical images for vision‑language models by scoring token importance with multiple cues and merging…
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)…
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…
REHRSeg: Unleashing the Power of Self-Supervised Super-Resolution for Resource-Efficient 3D MRI Segmentation
Zhiyun Song, Yinjie Zhao, Xiaomin Li +9
High-resolution (HR) 3D magnetic resonance imaging (MRI) can provide detailed anatomical structural information, enabling precise segmentation of regions of interest for various me…
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…
Emerging Threats in Deep Learning-Based Autonomous Driving: A Comprehensive Survey
Hui Cao, Wenlong Zou, Yinkun Wang +2
Since the 2004 DARPA Grand Challenge, the autonomous driving technology has witnessed nearly two decades of rapid development. Particularly, in recent years, with the application o…