94 citations · 162 across the 12 of their papers we have counts for
12 papers
Judge Like a Real Doctor: Dual Teacher Sample Consistency Framework for Semi-supervised Medical Image Classification
Zhang Qixiang, Yang Yuxiang, Zu Chen +4
Semi-supervised learning (SSL) is a popular solution to alleviate the high annotation cost in medical image classification. As a main branch of SSL, consistency regularization enga…
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…
Image2Points:A 3D Point-based Context Clusters GAN for High-Quality PET Image Reconstruction
Jiaqi Cui, Yan Wang, Lu Wen +4
To obtain high-quality Positron emission tomography (PET) images while minimizing radiation exposure, numerous methods have been proposed to reconstruct standard-dose PET (SPET) im…
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…
Contrastive Diffusion Model with Auxiliary Guidance for Coarse-to-Fine PET Reconstruction
Zeyu Han, Yuhan Wang, Luping Zhou +5
To obtain high-quality positron emission tomography (PET) scans while reducing radiation exposure to the human body, various approaches have been proposed to reconstruct standard-d…
TriDo-Former: A Triple-Domain Transformer for Direct PET Reconstruction from Low-Dose Sinograms
Jiaqi Cui, Pinxian Zeng, Xinyi Zeng +5
To obtain high-quality positron emission tomography (PET) images while minimizing radiation exposure, various methods have been proposed for reconstructing standard-dose PET (SPET)…
DiffDP: Radiotherapy Dose Prediction via a Diffusion Model
Zhenghao Feng, Lu Wen, Peng Wang +4
Currently, deep learning (DL) has achieved the automatic prediction of dose distribution in radiotherapy planning, enhancing its efficiency and quality. However, existing methods s…
Deep Learning based Multi-modal Computing with Feature Disentanglement for MRI Image Synthesis
Yuchen Fei, Bo Zhan, Mei Hong +3
Purpose: Different Magnetic resonance imaging (MRI) modalities of the same anatomical structure are required to present different pathological information from the physical level f…
ASMFS: Adaptive-Similarity-based Multi-modality Feature Selection for Classification of Alzheimer's Disease
Yuang Shi, Chen Zu, Mei Hong +6
With the increasing amounts of high-dimensional heterogeneous data to be processed, multi-modality feature selection has become an important research direction in medical image ana…
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,…