60 citations · 104 across the 15 of their papers we have counts for
10 papers · 1 filter
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)…
Tissue Segmentation of Thick-Slice Fetal Brain MR Scans with Guidance from High-Quality Isotropic Volumes
Shijie Huang, Xukun Zhang, Zhiming Cui +3
Accurate tissue segmentation of thick-slice fetal brain magnetic resonance (MR) scans is crucial for both reconstruction of isotropic brain MR volumes and the quantification of fet…
Multi-View Vertebra Localization and Identification from CT Images
Han Wu, Jiadong Zhang, Yu Fang +4
Accurately localizing and identifying vertebrae from CT images is crucial for various clinical applications. However, most existing efforts are performed on 3D with cropping patch…
Structure-aware registration network for liver DCE-CT images
Peng Xue, Jingyang Zhang, Lei Ma +7
Image registration of liver dynamic contrast-enhanced computed tomography (DCE-CT) is crucial for diagnosis and image-guided surgical planning of liver cancer. However, intensity v…
Geometry-Aware Attenuation Learning for Sparse-View CBCT Reconstruction
Zhentao Liu, Yu Fang, Changjian Li +4
Cone Beam Computed Tomography (CBCT) plays a vital role in clinical imaging. Traditional methods typically require hundreds of 2D X-ray projections to reconstruct a high-quality 3D…
Multi-scale Transformer Network with Edge-aware Pre-training for Cross-Modality MR Image Synthesis
Yonghao Li, Tao Zhou, Kelei He +2
Cross-modality magnetic resonance (MR) image synthesis can be used to generate missing modalities from given ones. Existing (supervised learning) methods often require a large numb…
SNAF: Sparse-view CBCT Reconstruction with Neural Attenuation Fields
Yu Fang, Lanzhuju Mei, Changjian Li +4
Cone beam computed tomography (CBCT) has been widely used in clinical practice, especially in dental clinics, while the radiation dose of X-rays when capturing has been a long conc…
JoJoNet: Joint-contrast and Joint-sampling-and-reconstruction Network for Multi-contrast MRI
Lin Zhao, Xiao Chen, Eric Z. Chen +4
Multi-contrast Magnetic Resonance Imaging (MRI) generates multiple medical images with rich and complementary information for routine clinical use; however, it suffers from a long…
Learning towards Synchronous Network Memorizability and Generalizability for Continual Segmentation across Multiple Sites
Jingyang Zhang, Peng Xue, Ran Gu +7
In clinical practice, a segmentation network is often required to continually learn on a sequential data stream from multiple sites rather than a consolidated set, due to the stora…