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Deep Efficient End-to-end Reconstruction (DEER) Network for Few-view Breast CT Image Reconstruction
Huidong Xie, Hongming Shan, Wenxiang Cong +5
Breast CT provides image volumes with isotropic resolution in high contrast, enabling detection of small calcification (down to a few hundred microns in size) and subtle density di…
Deep Encoder-decoder Adversarial Reconstruction (DEAR) Network for 3D CT from Few-view Data
Huidong Xie, Hongming Shan, Ge Wang
X-ray computed tomography (CT) is widely used in clinical practice. The involved ionizing X-ray radiation, however, could increase cancer risk. Hence, the reduction of the radiatio…
Parameter-Transferred Wasserstein Generative Adversarial Network (PT-WGAN) for Low-Dose PET Image Denoising
Yu Gong, Hongming Shan, Yueyang Teng +5
Due to the widespread use of positron emission tomography (PET) in clinical practice, the potential risk of PET-associated radiation dose to patients needs to be minimized. However…
Multi-Contrast Super-Resolution MRI Through a Progressive Network
Qing Lyu, Hongming Shan, Ge Wang
Magnetic resonance imaging (MRI) is widely used for screening, diagnosis, image-guided therapy, and scientific research. A significant advantage of MRI over other imaging modalitie…
MRI Super-Resolution with Ensemble Learning and Complementary Priors
Qing Lyu, Hongming Shan, Ge Wang
Magnetic resonance imaging (MRI) is a widely used medical imaging modality. However, due to the limitations in hardware, scan time, and throughput, it is often clinically challengi…
Dual Network Architecture for Few-view CT -- Trained on ImageNet Data and Transferred for Medical Imaging
Huidong Xie, Hongming Shan, Wenxiang Cong +4
X-ray computed tomography (CT) reconstructs cross-sectional images from projection data. However, ionizing X-ray radiation associated with CT scanning might induce cancer and genet…