5 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…
FDDM: Frequency-Decomposed Diffusion Model for Rectum Cancer Dose Prediction in Radiotherapy
Xin Liao, Zhenghao Feng, Jianghong Xiao +2
Accurate dose distribution prediction is crucial in the radiotherapy planning. Although previous methods based on convolutional neural network have shown promising performance, the…
BTMuda: A Bi-level Multi-source unsupervised domain adaptation framework for breast cancer diagnosis
Yuxiang Yang, Xinyi Zeng, Pinxian Zeng +4
Deep learning has revolutionized the early detection of breast cancer, resulting in a significant decrease in mortality rates. However, difficulties in obtaining annotations and hu…
Alleviating Class Imbalance in Semi-supervised Multi-organ Segmentation via Balanced Subclass Regularization
Zhenghao Feng, Lu Wen, Binyu Yan +2
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…
ARANet: Attention-based Residual Adversarial Network with Deep Supervision for Radiotherapy Dose Prediction of Cervical Cancer
Lu Wen, Wenxia Yin, Zhenghao Feng +3
Radiation therapy is the mainstay treatment for cervical cancer, and its ultimate goal is to ensure the planning target volume (PTV) reaches the prescribed dose while reducing dose…