10 citations · 29 across the 16 of their papers we have counts for
5 papers · 1 filter
Re-Visible Dual-Domain Self-Supervised Deep Unfolding Network for MRI Reconstruction
Hao Zhang, Qi Wang, Jian Sun +3
Magnetic Resonance Imaging (MRI) is widely used in clinical practice, but suffered from prolonged acquisition time. Although deep learning methods have been proposed to accelerate…
Deep Unfolding Network with Spatial Alignment for multi-modal MRI reconstruction
Hao Zhang, Qi Wang, Jun Shi +2
Multi-modal Magnetic Resonance Imaging (MRI) offers complementary diagnostic information, but some modalities are limited by the long scanning time. To accelerate the whole acquisi…
Weakly Supervised Lesion Detection and Diagnosis for Breast Cancers with Partially Annotated Ultrasound Images
Jian Wang, Liang Qiao, Shichong Zhou +6
Deep learning (DL) has proven highly effective for ultrasound-based computer-aided diagnosis (CAD) of breast cancers. In an automaticCAD system, lesion detection is critical for th…
Spatial and Modal Optimal Transport for Fast Cross-Modal MRI Reconstruction
Qi Wang, Zhijie Wen, Jun Shi +3
Multi-modal magnetic resonance imaging (MRI) plays a crucial role in comprehensive disease diagnosis in clinical medicine. However, acquiring certain modalities, such as T2-weighte…
Fast MRI Reconstruction via Edge Attention
Hanhui Yang, Juncheng Li, Lok Ming Lui +3
Fast and accurate MRI reconstruction is a key concern in modern clinical practice. Recently, numerous Deep-Learning methods have been proposed for MRI reconstruction, however, they…