427 citations · 3.3k across the 77 of their papers we have counts for
14 papers · 1 filter
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…
Look globally, age locally: Face aging with an attention mechanism
Haiping Zhu, Zhizhong Huang, Hongming Shan +1
Face aging is of great importance for cross-age recognition and entertainment-related applications. Recently, conditional generative adversarial networks (cGANs) have achieved impr…
Deep learning for accelerating Monte Carlo radiation transport simulation in intensity-modulated radiation therapy
Zhao Peng, Hongming Shan, Tianyu Liu +4
Cancer is a primary cause of morbidity and mortality worldwide. The radiotherapy plays a more and more important role in cancer treatment. In the radiotherapy, the dose distributio…
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…
A Method of Rapid Quantification of Patient-Specific Organ Dose for CT Using Coupled Deep-Learning based Multi-Organ Segmentation and GPU-accelerated Monte Carlo Dose Computing
Zhao Peng, Xi Fang, Pingkun Yan +7
Purpose: This paper describes a new method to apply deep-learning algorithms for automatic segmentation of radiosensitive organs from 3D tomographic CT images before computing orga…
Deep-learning-based Breast CT for Radiation Dose Reduction
Wenxiang Cong, Hongming Shan, Xiaohua Zhang +3
Cone-beam breast computed tomography (CT) provides true 3D breast images with isotropic resolution and high-contrast information, detecting calcifications as small as a few hundred…
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…
Simultaneous reconstruction of the initial pressure and sound speed in photoacoustic tomography using a deep-learning approach
Hongming Shan, Christopher Wiedeman, Ge Wang +1
Photoacoustic tomography seeks to reconstruct an acoustic initial pressure distribution from the measurement of the ultrasound waveforms. Conventional methods assume a-prior knowle…
Precipitation Nowcasting with Star-Bridge Networks
Yuan Cao, Qiuying Li, Hongming Shan +4
Precipitation nowcasting, which aims to precisely predict the short-term rainfall intensity of a local region, is gaining increasing attention in the artificial intelligence commun…
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…
Ordinal Distribution Regression for Gait-based Age Estimation
Haiping Zhu, Yuheng Zhang, Guohao Li +2
Computer vision researchers prefer to estimate age from face images because facial features provide useful information. However, estimating age from face images becomes challenging…
Quadratic Autoencoder (Q-AE) for Low-dose CT Denoising
Fenglei Fan, Hongming Shan, Mannudeep K. Kalra +6
Inspired by complexity and diversity of biological neurons, our group proposed quadratic neurons by replacing the inner product in current artificial neurons with a quadratic opera…