101 citations · 313 across the 10 of their papers we have counts for
Showing 2019Show all
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eess.IV2019★ 91 cited
Fully Automated Multi-Organ Segmentation in Abdominal Magnetic Resonance Imaging with Deep Neural Networks
Yuhua Chen, Dan Ruan, Jiayu Xiao +6
Segmentation of multiple organs-at-risk (OARs) is essential for radiation therapy treatment planning and other clinical applications. We developed an Automated deep Learning-based…
physics.med-ph2019★ 54 cited
Generation of abdominal synthetic CTs from 0.35T MR images using generative adversarial networks for MR-only liver radiotherapy
Jie Fu, Kamal Singhrao, Minsong Cao +7
Electron density maps must be accurately estimated to achieve valid dose calculation in MR-only radiotherapy. The goal of this study is to assess whether two deep learning models,…
cs.CV2019★ 10 cited
Fully Automated Pancreas Segmentation with Two-stage 3D Convolutional Neural Networks
Ningning Zhao, Nuo Tong, Dan Ruan +1
Due to the fact that pancreas is an abdominal organ with very large variations in shape and size, automatic and accurate pancreas segmentation can be challenging for medical image…