60 citations · 104 across the 15 of their papers we have counts for
15 papers
Taming foundation model with invariance-oriented pre-training for broad-spectrum EEG analysis across signal-level, brain-state, and brain-health tasks
Yulong Dou, Han Wu, Guo Chen +3
Electroencephalography (EEG) is a widely used window into human brain function, but most EEG models remain tied to a one-dataset-one-model supervised paradigm. Recent EEG foundatio…
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…
Accurate 3D Prediction of Missing Teeth in Diverse Patterns for Precise Dental Implant Planning
Lei Ma, Peng Xue, Yuning Gu +4
In recent years, the demand for dental implants has surged, driven by their high success rates and esthetic advantages. However, accurate prediction of missing teeth for precise di…
Construction of unbiased dental template and parametric dental model for precision digital dentistry
Lei Ma, Jingyang Zhang, Ke Deng +8
Dental template and parametric dental models are important tools for various applications in digital dentistry. However, constructing an unbiased dental template and accurate param…
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…
NeuroExplainer: Fine-Grained Attention Decoding to Uncover Cortical Development Patterns of Preterm Infants
Chenyu Xue, Fan Wang, Yuanzhuo Zhu +4
Deploying reliable deep learning techniques in interdisciplinary applications needs learned models to output accurate and (even more importantly) explainable predictions. Existing…
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…
Forecasting Human Trajectory from Scene History
Mancheng Meng, Ziyan Wu, Terrence Chen +4
Predicting the future trajectory of a person remains a challenging problem, due to randomness and subjectivity of human movement. However, the moving patterns of human in a constra…
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…