11 citations · 20 across the 9 of their papers we have counts for
9 papers
BASIC: Semi-supervised Multi-organ Segmentation with Balanced Subclass Regularization and Semantic-conflict Penalty
Zhenghao Feng, Lu Wen, Yuanyuan Xu +4
Semi-supervised learning (SSL) has shown notable potential in relieving the heavy demand of dense prediction tasks on large-scale well-annotated datasets, especially for the challe…
MCAD: Multi-modal Conditioned Adversarial Diffusion Model for High-Quality PET Image Reconstruction
Jiaqi Cui, Xinyi Zeng, Pinxian Zeng +4
Radiation hazards associated with standard-dose positron emission tomography (SPET) images remain a concern, whereas the quality of low-dose PET (LPET) images fails to meet clinica…
Adaptive Prompt Learning with Negative Textual Semantics and Uncertainty Modeling for Universal Multi-Source Domain Adaptation
Yuxiang Yang, Lu Wen, Yuanyuan Xu +2
Universal Multi-source Domain Adaptation (UniMDA) transfers knowledge from multiple labeled source domains to an unlabeled target domain under domain shifts (different data distrib…
Two-Phase Multi-Dose-Level PET Image Reconstruction with Dose Level Awareness
Yuchen Fei, Yanmei Luo, Yan Wang +4
To obtain high-quality positron emission tomography (PET) while minimizing radiation exposure, a range of methods have been designed to reconstruct standard-dose PET (SPET) from co…
Dcl-Net: Dual Contrastive Learning Network for Semi-Supervised Multi-Organ Segmentation
Lu Wen, Zhenghao Feng, Yun Hou +4
Semi-supervised learning is a sound measure to relieve the strict demand of abundant annotated datasets, especially for challenging multi-organ segmentation . However, most existin…
Triplet-constraint Transformer with Multi-scale Refinement for Dose Prediction in Radiotherapy
Lu Wen, Qihun Zhang, Zhenghao Feng +4
Radiotherapy is a primary treatment for cancers with the aim of applying sufficient radiation dose to the planning target volume (PTV) while minimizing dose hazards to the organs a…