85 citations · 122 across the 12 of their papers we have counts for
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cs.CV2018★ 85 cited
Predicting Lung Nodule Malignancies by Combining Deep Convolutional Neural Network and Handcrafted Features
Shulong Li, Panpan Xu, Bin Li +8
To predict lung nodule malignancy with a high sensitivity and specificity, we propose a fusion algorithm that combines handcrafted features (HF) into the features learned at the ou…
cs.CV2018★ 3 cited
Radon Inversion via Deep Learning
Ji He, Jianhua Ma
Radon transform is widely used in physical and life sciences and one of its major applications is the X-ray computed tomography (X-ray CT), which is significant in modern health ex…
cs.CV2018★ 12 cited
Unsupervised/Semi-supervised Deep Learning for Low-dose CT Enhancement
Mingrui Geng, Yun Deng, Qian Zhao +4
Recently, deep learning(DL) methods have been proposed for the low-dose computed tomography(LdCT) enhancement, and obtain good trade-off between computational efficiency and image…