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Wen Li et al.
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Abass Bahrami et al.
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Reko Kemppainen et al.
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Ghazal Shafai-Erfani et al.
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Pseudo-CT image generation from mDixon MRI images using fully convolutional neural networks
J. Stadelmann et al.
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Mateusz C. Florkow et al.
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The rationale for MR-only treatment planning for external radiotherapy
Joakim Jonsson et al.
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MRI-based treatment planning for proton radiotherapy: dosimetric validation of a deep learning-based liver synthetic CT generation method
Yingzi Liu et al.
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Survey on deep learning for radiotherapy
Philippe Meyer et al.
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Emily Johnstone et al.
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Anna M. Dinkla et al.
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Tufve Nyholm et al.
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Hajar Emami et al.
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Shupeng Chen et al.
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Heran Yang et al.
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Matteo Maspero et al.
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Amir M. Owrangi et al.
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SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
Vijay Badrinarayanan et al.
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Z Wang et al.
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New variants of a method of MRI scale standardization
LG Nyúl et al.
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