Jun-Wu Zhong

collaborators

2 papers

cs.CV2025

ERANet: Edge Replacement Augmentation for Semi-Supervised Meniscus Segmentation with Prototype Consistency Alignment and Conditional Self-Training

Siyue Li, Yongcheng Yao, Junru Zhong +9

Manual segmentation is labor-intensive, and automatic segmentation remains challenging due to the inherent variability in meniscal morphology, partial volume effects, and low contr…

eess.IV2025

Utilizing 3D Fast Spin Echo Anatomical Imaging to Reduce the Number of Contrast Preparations in $T_{1 I ¨ }$ Quantification of Knee Cartilage Using Learning-Based Methods

Junru Zhong, Chaoxing Huang, Ziqiang Yu +7

Purpose: To propose and evaluate an accelerated $T_{1 I ¨ }$ quantification method that combines $T_{1 I ¨ }$ -weighted fast spin echo (FSE) images and proton density (PD)-weighted anatom…

ERANet: Edge Replacement Augmentation for Semi-Supervised Meniscus Segmentation with Prototype Consistency Alignment and Conditional Self-Training

Utilizing 3D Fast Spin Echo Anatomical Imaging to Reduce the Number of Contrast Preparations in T1I¨​ Quantification of Knee Cartilage Using Learning-Based Methods

Utilizing 3D Fast Spin Echo Anatomical Imaging to Reduce the Number of Contrast Preparations in $T_{1 I ¨ }$ Quantification of Knee Cartilage Using Learning-Based Methods