MR-based synthetic CT generation using a deep convolutional neural network method.
about
A parallel MR imaging method using multilayer perceptron.Direct PseudoCT Generation for Pelvis PET/MRI Attenuation Correction using Deep Convolutional Neural Networks with Multi-parametric MRI: Zero Echo-time and Dixon Deep pseudoCT (ZeDD-CT).MRI-only treatment planning: benefits and challenges.Automatic segmentation of the clinical target volume and organs at risk in the planning CT for rectal cancer using deep dilated convolutional neural networks.Deep Deconvolutional Neural Network for Target Segmentation of Nasopharyngeal Cancer in Planning Computed Tomography Images.Automatic classification of ovarian cancer types from cytological images using deep convolutional neural networks.Deep-learned 3D black-blood imaging using automatic labelling technique and 3D convolutional neural networks for detecting metastatic brain tumors.Cone Beam Computed Tomography Image Quality Improvement Using a Deep Convolutional Neural Network.
P2860
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P2860
MR-based synthetic CT generation using a deep convolutional neural network method.
description
2017 nî lūn-bûn
@nan
2017年の論文
@ja
2017年論文
@yue
2017年論文
@zh-hant
2017年論文
@zh-hk
2017年論文
@zh-mo
2017年論文
@zh-tw
2017年论文
@wuu
2017年论文
@zh
2017年论文
@zh-cn
name
MR-based synthetic CT generation using a deep convolutional neural network method.
@en
type
label
MR-based synthetic CT generation using a deep convolutional neural network method.
@en
prefLabel
MR-based synthetic CT generation using a deep convolutional neural network method.
@en
P2860
P921
P356
P1433
P1476
MR-based synthetic CT generation using a deep convolutional neural network method.
@en
P2093
P2860
P304
P356
10.1002/MP.12155
P407
P577
2017-02-13T00:00:00Z
P698
P818
1704.07239