2 citations · 3 across the 2 of their papers we have counts for
4 papers
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…
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…