21 citations · 57 across the 5 of their papers we have counts for
6 papers · 1 filter
SAINT: Spatially Aware Interpolation NeTwork for Medical Slice Synthesis
Cheng Peng, Wei-An Lin, Haofu Liao +2
Deep learning-based single image super-resolution (SISR) methods face various challenges when applied to 3D medical volumetric data (i.e., CT and MR images) due to the high memory…
Encoding Metal Mask Projection for Metal Artifact Reduction in Computed Tomography
Yuanyuan Lyu, Wei-An Lin, Haofu Liao +2
Metal artifact reduction (MAR) in computed tomography (CT) is a notoriously challenging task because the artifacts are structured and non-local in the image domain. However, they a…
Towards multi-sequence MR image recovery from undersampled k-space data
Cheng Peng, Wei-An Lin, Rama Chellappa +1
Undersampled MR image recovery has been widely studied for accelerated MR acquisition. However, it has been mostly studied under a single sequence scenario, despite the fact that m…
Deep Slice Interpolation via Marginal Super-Resolution, Fusion and Refinement
Cheng Peng, Wei-An Lin, Haofu Liao +2
We propose a marginal super-resolution (MSR) approach based on 2D convolutional neural networks (CNNs) for interpolating an anisotropic brain magnetic resonance scan along the high…
ADN: Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction
Haofu Liao, Wei-An Lin, S. Kevin Zhou +1
Current deep neural network based approaches to computed tomography (CT) metal artifact reduction (MAR) are supervised methods that rely on synthesized metal artifacts for training…
DuDoNet: Dual Domain Network for CT Metal Artifact Reduction
Wei-An Lin, Haofu Liao, Cheng Peng +5
Computed tomography (CT) is an imaging modality widely used for medical diagnosis and treatment. CT images are often corrupted by undesirable artifacts when metallic implants are c…