1 citations · 1 across the 4 of their papers we have counts for
5 papers
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…
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…
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…
Polymerized Feature-based Domain Adaptation for Cervical Cancer Dose Map Prediction
Jie Zeng, Zeyu Han, Xingchen Peng +3
Recently, deep learning (DL) has automated and accelerated the clinical radiation therapy (RT) planning significantly by predicting accurate dose maps. However, most DL-based dose…
DSU-net: Dense SegU-net for automatic head-and-neck tumor segmentation in MR images
Pin Tang, Chen Zu, Mei Hong +7
Precise and accurate segmentation of the most common head-and-neck tumor, nasopharyngeal carcinoma (NPC), in MRI sheds light on treatment and regulatory decisions making. However,…