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Soft Autoencoder and Its Wavelet Adaptation Interpretation
Fenglei Fan, Mengzhou Li, Yueyang Teng +1
Recently, deep learning becomes the main focus of machine learning research and has greatly impacted many important fields. However, deep learning is criticized for lack of interpr…
Can Deep Learning Outperform Modern Commercial CT Image Reconstruction Methods?
Hongming Shan, Atul Padole, Fatemeh Homayounieh +5
Commercial iterative reconstruction techniques on modern CT scanners target radiation dose reduction but there are lingering concerns over their impact on image appearance and low…
Low-Dose CT via Deep CNN with Skip Connection and Network in Network
Chenyu You, Linfeng Yang, Yi Zhang +1
A major challenge in computed tomography (CT) is how to minimize patient radiation exposure without compromising image quality and diagnostic performance. The use of deep convoluti…
On a Sparse Shortcut Topology of Artificial Neural Networks
Fenglei Fan, Dayang Wang, Hengtao Guo +4
In established network architectures, shortcut connections are often used to take the outputs of earlier layers as additional inputs to later layers. Despite the extraordinary effe…
Hybrid deep neural networks for all-cause Mortality Prediction from LDCT Images
Pingkun Yan, Hengtao Guo, Ge Wang +2
Known for its high morbidity and mortality rates, lung cancer poses a significant threat to human health and well-being. However, the same population is also at high risk for other…
Super-resolution MRI through Deep Learning
Qing Lyu, Chenyu You, Hongming Shan +1
Magnetic resonance imaging (MRI) is extensively used for diagnosis and image-guided therapeutics. Due to hardware, physical and physiological limitations, acquisition of high-resol…