356 citations · 799 across the 42 of their papers we have counts for
7 papers · 1 filter
Clinical Micro-CT Empowered by Interior Tomography, Robotic Scanning, and Deep Learning
Mengzhou Li, Zheng Fang, Wenxiang Cong +6
While micro-CT systems are instrumental in preclinical research, clinical micro-CT imaging has long been desired with cochlear implantation as a primary example. The structural det…
Suppression of Correlated Noise with Similarity-based Unsupervised Deep Learning
Chuang Niu, Mengzhou Li, Fenglei Fan +4
Image denoising is a prerequisite for downstream tasks in many fields. Low-dose and photon-counting computed tomography (CT) denoising can optimize diagnostic performance at minimi…
Self-supervised Representation Learning for Evolutionary Neural Architecture Search
Chen Wei, Yiping Tang, Chuang Niu +3
Recently proposed neural architecture search (NAS) algorithms adopt neural predictors to accelerate the architecture search. The capability of neural predictors to accurately predi…
Deep Learning based Spectral CT Imaging
Weiwen Wu, Dianlin Hu, Chuang Niu +7
Spectral computed tomography (CT) has attracted much attention in radiation dose reduction, metal artifacts removal, tissue quantification and material discrimination. The x-ray en…
Stabilizing Deep Tomographic Reconstruction
Weiwen Wu, Dianlin Hu, Wenxiang Cong +7
Tomographic image reconstruction with deep learning is an emerging field, but a recent landmark study reveals that several deep reconstruction networks are unstable for computed to…
Low-dimensional Manifold Constrained Disentanglement Network for Metal Artifact Reduction
Chuang Niu, Wenxiang Cong, Fenglei Fan +4
Deep neural network based methods have achieved promising results for CT metal artifact reduction (MAR), most of which use many synthesized paired images for training. As synthesiz…
GATCluster: Self-Supervised Gaussian-Attention Network for Image Clustering
Chuang Niu, Jun Zhang, Ge Wang +1
We propose a self-supervised Gaussian ATtention network for image Clustering (GATCluster). Rather than extracting intermediate features first and then performing the traditional cl…