4 papers
SpecNet: Spectral Domain Convolutional Neural Network
Bochen Guan, Jinnian Zhang, William A. Sethares +2
The memory consumption of most Convolutional Neural Network (CNN) architectures grows rapidly with increasing depth of the network, which is a major constraint for efficient networ…
SANTIS: Sampling-Augmented Neural neTwork with Incoherent Structure for MR image reconstruction
Fang Liu, Lihua Chen, Richard Kijowski +1
Deep learning holds great promise in the reconstruction of undersampled Magnetic Resonance Imaging (MRI) data, providing new opportunities to escalate the performance of rapid MRI.…
SUSAN: Segment Unannotated image Structure using Adversarial Network
Fang Liu
Segmentation of magnetic resonance (MR) images is a fundamental step in many medical imaging-based applications. The recent implementation of deep convolutional neural networks (CN…
MANTIS: Model-Augmented Neural neTwork with Incoherent k-space Sampling for efficient MR T2 mapping
Fang Liu, Li Feng, Richard Kijowski
Quantitative mapping of magnetic resonance (MR) parameters have been shown as valuable methods for improved assessment of a range of diseases. Due to the need to image an anatomic…