most citedMulti-Level Global Context Cross Consistency Model for Semi-Supervised Ultrasound Image Segmentation with Diffusion Model

14 citations · 24 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

HySparK: Hybrid Sparse Masking for Large Scale Medical Image Pre-Training

Fenghe Tang, Ronghao Xu, Qingsong Yao +5

The generative self-supervised learning strategy exhibits remarkable learning representational capabilities. However, there is limited attention to end-to-end pre-training methods…

cs.CV2024

APPLE: Adversarial Privacy-aware Perturbations on Latent Embedding for Unfairness Mitigation

Zikang Xu, Fenghe Tang, Quan Quan +2

Ensuring fairness in deep-learning-based segmentors is crucial for health equity. Much effort has been dedicated to mitigating unfairness in the training datasets or procedures. Ho…

eess.IV20239 cited

CMUNeXt: An Efficient Medical Image Segmentation Network based on Large Kernel and Skip Fusion

Fenghe Tang, Jianrui Ding, Lingtao Wang +2

The U-shaped architecture has emerged as a crucial paradigm in the design of medical image segmentation networks. However, due to the inherent local limitations of convolution, a f…

cs.CV20231 cited

Thinking Twice: Clinical-Inspired Thyroid Ultrasound Lesion Detection Based on Feature Feedback

Lingtao Wang, Jianrui Ding, Fenghe Tang +1

Accurate detection of thyroid lesions is a critical aspect of computer-aided diagnosis. However, most existing detection methods perform only one feature extraction process and the…

cs.CV202314 cited

Multi-Level Global Context Cross Consistency Model for Semi-Supervised Ultrasound Image Segmentation with Diffusion Model

Fenghe Tang, Jianrui Ding, Lingtao Wang +2

Medical image segmentation is a critical step in computer-aided diagnosis, and convolutional neural networks are popular segmentation networks nowadays. However, the inherent local…