2 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.CV2024
HResFormer: Hybrid Residual Transformer for Volumetric Medical Image Segmentation
Sucheng Ren, Xiaomeng Li
Vision Transformer shows great superiority in medical image segmentation due to the ability in learning long-range dependency. For medical image segmentation from 3D data, such as…
cs.CV2024★ 2 cited
S&D Messenger: Exchanging Semantic and Domain Knowledge for Generic Semi-Supervised Medical Image Segmentation
Qixiang Zhang, Haonan Wang, Xiaomeng Li
Semi-supervised medical image segmentation (SSMIS) has emerged as a promising solution to tackle the challenges of time-consuming manual labeling in the medical field. However, in…
cs.CV2024★ 2 cited
AllSpark: Reborn Labeled Features from Unlabeled in Transformer for Semi-Supervised Semantic Segmentation
Haonan Wang, Qixiang Zhang, Yi Li +1
Semi-supervised semantic segmentation (SSSS) has been proposed to alleviate the burden of time-consuming pixel-level manual labeling, which leverages limited labeled data along wit…