114 citations · 226 across the 8 of their papers we have counts for
8 papers
Cross-supervised Dual Classifiers for Semi-supervised Medical Image Segmentation
Zhenxi Zhang, Ran Ran, Chunna Tian +4
Semi-supervised medical image segmentation offers a promising solution for large-scale medical image analysis by significantly reducing the annotation burden while achieving compar…
Self-aware and Cross-sample Prototypical Learning for Semi-supervised Medical Image Segmentation
Zhenxi Zhang, Ran Ran, Chunna Tian +4
Consistency learning plays a crucial role in semi-supervised medical image segmentation as it enables the effective utilization of limited annotated data while leveraging the abund…
Position-Aware Relation Learning for RGB-Thermal Salient Object Detection
Heng Zhou, Chunna Tian, Zhenxi Zhang +4
RGB-Thermal salient object detection (SOD) combines two spectra to segment visually conspicuous regions in images. Most existing methods use boundary maps to learn the sharp bounda…
Mutual- and Self- Prototype Alignment for Semi-supervised Medical Image Segmentation
Zhenxi Zhang, Chunna Tian, Zhicheng Jiao
Semi-supervised learning methods have been explored in medical image segmentation tasks due to the scarcity of pixel-level annotation in the real scenario. Proto-type alignment bas…
PixelGame: Infrared small target segmentation as a Nash equilibrium
Heng Zhou, Chunna Tian, Zhenxi Zhang +3
A key challenge of infrared small target segmentation (ISTS) is to balance false negative pixels (FNs) and false positive pixels (FPs). Traditional methods combine FNs and FPs into…
Collaborative Boundary-aware Context Encoding Networks for Error Map Prediction
Zhenxi Zhang, Chunna Tian, Jie Li +3
Medical image segmentation is usually regarded as one of the most important intermediate steps in clinical situations and medical imaging research. Thus, accurately assessing the s…
A sparse annotation strategy based on attention-guided active learning for 3D medical image segmentation
Zhenxi Zhang, Jie Li, Zhusi Zhong +2
3D image segmentation is one of the most important and ubiquitous problems in medical image processing. It provides detailed quantitative analysis for accurate disease diagnosis, a…
An Attention-Guided Deep Regression Model for Landmark Detection in Cephalograms
Zhusi Zhong, Jie Li, Zhenxi Zhang +2
Cephalometric tracing method is usually used in orthodontic diagnosis and treatment planning. In this paper, we propose a deep learning based framework to automatically detect anat…