1.9k citations · 6.7k across the 80 of their papers we have counts for
6 papers · 2 filters
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…
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…
Shape and Margin-Aware Lung Nodule Classification in Low-dose CT Images via Soft Activation Mapping
Yiming Lei, Yukun Tian, Hongming Shan +3
A number of studies on lung nodule classification lack clinical/biological interpretations of the features extracted by convolutional neural network (CNN). The methods like class a…
Structure-sensitive Multi-scale Deep Neural Network for Low-Dose CT Denoising
Chenyu You, Qingsong Yang, Hongming Shan +8
Computed tomography (CT) is a popular medical imaging modality in clinical applications. At the same time, the x-ray radiation dose associated with CT scans raises public concerns…
3D Convolutional Encoder-Decoder Network for Low-Dose CT via Transfer Learning from a 2D Trained Network
Hongming Shan, Yi Zhang, Qingsong Yang +5
Low-dose computed tomography (CT) has attracted a major attention in the medical imaging field, since CT-associated x-ray radiation carries health risks for patients. The reduction…