1 citations · 2 across the 8 of their papers we have counts for
8 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…
S3PET: Semi-supervised Standard-dose PET Image Reconstruction via Dose-aware Token Swap
Jiaqi Cui, Pinxian Zeng, Yuanyuan Xu +3
To acquire high-quality positron emission tomography (PET) images while reducing the radiation tracer dose, numerous efforts have been devoted to reconstructing standard-dose PET (…
Learning with Alignments: Tackling the Inter- and Intra-domain Shifts for Cross-multidomain Facial Expression Recognition
Yuxiang Yang, Lu Wen, Xinyi Zeng +4
Facial Expression Recognition (FER) holds significant importance in human-computer interactions. Existing cross-domain FER methods often transfer knowledge solely from a single lab…
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…
Dose Prediction Driven Radiotherapy Paramters Regression via Intra- and Inter-Relation Modeling
Jiaqi Cui, Yuanyuan Xu, Jianghong Xiao +4
Deep learning has facilitated the automation of radiotherapy by predicting accurate dose distribution maps. However, existing methods fail to derive the desirable radiotherapy para…
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…
Diffusion-based Radiotherapy Dose Prediction Guided by Inter-slice Aware Structure Encoding
Zhenghao Feng, Lu Wen, Jianghong Xiao +5
Deep learning (DL) has successfully automated dose distribution prediction in radiotherapy planning, enhancing both efficiency and quality. However, existing methods suffer from th…