Siyue Li

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

3 citations · 6 across the 5 of their papers we have counts for

collaborators

Showing eess.IVShow all

3 papers · 1 filter

eess.IV2025★ 2 cited

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

Junru Zhong, Chaoxing Huang, Ziqiang Yu +7

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

eess.IV2025★ 1 cited

DGSSA: Domain generalization with structural and stylistic augmentation for retinal vessel segmentation

Bo Liu, Yudong Zhang, Shuihua Wang +2

Retinal vascular morphology is crucial for diagnosing diseases such as diabetes, glaucoma, and hypertension, making accurate segmentation of retinal vessels essential for early int…

eess.IV2024

A Systematic Post-Processing Approach for Quantitative $T_{1 ρ}$ Imaging of Knee Articular Cartilage

Junru Zhong, Yongcheng Yao, Fan Xiao +7

Objective: To establish an automated pipeline for post-processing of quantitative spin-lattice relaxation time constant in the rotating frame ( $T_{1 ρ}$ ) imaging of knee articular c…

Utilizing 3D Fast Spin Echo Anatomical Imaging to Reduce the Number of Contrast Preparations in T1ρ​ Quantification of Knee Cartilage Using Learning-Based Methods

DGSSA: Domain generalization with structural and stylistic augmentation for retinal vessel segmentation

A Systematic Post-Processing Approach for Quantitative T1ρ​ Imaging of Knee Articular Cartilage

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

A Systematic Post-Processing Approach for Quantitative $T_{1 ρ}$ Imaging of Knee Articular Cartilage