1 citations · 1 across the 2 of their papers we have counts for
7 papers
Recover Semantics First, Generate Better: Improved Latent Modeling for 3D MRI Reconstruction and Cross-Contrast Synthesis
Yonghao Chen, Sicheng Yang, Rui Tang +1
Multi-contrast magnetic resonance imaging (MRI) provides complementary information for clinical diagnosis. However, acquiring all MRI sequences is often time-consuming and costly.…
SegDINO: Introducing Multi-Scale Structure into DINO for Efficient Medical Image Segmentation
Sicheng Yang, Hongqiu Wang, Zhaohu Xing +5
Self-supervised DINO models provide strong transferable visual representations, yet applying them directly to image segmentation remains challenging. Existing approaches commonly r…
VQ-Seg: Vector-Quantized Token Perturbation for Semi-Supervised Medical Image Segmentation
Sicheng Yang, Zhaohu Xing, Lei Zhu
Consistency learning with feature perturbation is a widely used strategy in semi-supervised medical image segmentation. However, many existing perturbation methods rely on dropout,…
VAEVQ: Enhancing Discrete Visual Tokenization through Variational Modeling
Sicheng Yang, Xing Hu, Qiang Wu +1
Vector quantization (VQ) transforms continuous image features into discrete representations, providing compressed, tokenized inputs for generative models. However, VQ-based framewo…
K-Stain: Keypoint-Driven Correspondence for H&E-to-IHC Virtual Staining
Sicheng Yang, Zhaohu Xing, Haipeng Zhou +1
Virtual staining offers a promising method for converting Hematoxylin and Eosin (H&E) images into Immunohistochemical (IHC) images, eliminating the need for costly chemical process…
SegDINO: An Efficient Design for Medical and Natural Image Segmentation with DINO-V3
Sicheng Yang, Hongqiu Wang, Zhaohu Xing +2
The DINO family of self-supervised vision models has shown remarkable transferability, yet effectively adapting their representations for segmentation remains challenging. Existing…