A hierarchical approach to deep learning and its application to tomographic reconstruction

16 December 2019

Papers citing "A hierarchical approach to deep learning and its application to tomographic reconstruction"

9 / 9 papers shown

Title
Low Dose CT Image Denoising Using a Generative Adversarial Network with Wasserstein Distance and Perceptual Loss Qingsong Yang Pingkun Yan Yanbo Zhang Hengyong Yu Yongyi Shi X. Mou Mannudeep K. Kalra Ge Wang GAN MedIm 58 1,193 0 03 Aug 2017
A Cascaded Convolutional Neural Network for X-ray Low-dose CT Image Denoising Dufan Wu Kyungsang Kim Xiaofeng Liu Quanzheng Li MedIm OOD 74 65 0 11 May 2017
Image reconstruction by domain transform manifold learning Bo Zhu Jeremiah Zhe Liu Bruce Rosen Matthew S. Rosen 77 1,525 0 28 Apr 2017
Learning a Variational Network for Reconstruction of Accelerated MRI Data Kerstin Hammernik Teresa Klatzer Erich Kobler M. Recht D. Sodickson Thomas Pock Florian Knoll 43 1,535 0 03 Apr 2017
Deep Convolutional Neural Network for Inverse Problems in Imaging Kyong Hwan Jin Michael T. McCann Emmanuel Froustey M. Unser 42 2,116 0 11 Nov 2016
A deep convolutional neural network using directional wavelets for low-dose X-ray CT reconstruction Eunhee Kang Junhong Min J. C. Ye OOD MedIm 50 763 0 31 Oct 2016
A Perspective on Deep Imaging Ge Wang OOD 37 391 0 10 Sep 2016
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation Vijay Badrinarayanan Alex Kendall R. Cipolla SSeg 775 15,718 0 02 Nov 2015
Rich feature hierarchies for accurate object detection and semantic segmentation Ross B. Girshick Jeff Donahue Trevor Darrell Jitendra Malik ObjD 224 26,122 0 11 Nov 2013