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Synergizing medical imaging and radiotherapy with deep learning

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IOP Publishing Ltd
DOI: 10.1088/2632-2153/ab869f

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  1. NIH/NCI [R01CA233888, R01CA237267, R01CA227289, R37CA214639, R01CA237269]
  2. NIH/NIBIB [R01EB026646]

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This article reviews deep learning methods for medical imaging (focusing on image reconstruction, segmentation, registration, and radiomics) and radiotherapy (ranging from planning and verification to prediction) as well as the connections between them. Then, future topics are discussed involving semantic analysis through natural language processing and graph neural networks. It is believed that deep learning in particular, and artificial intelligence and machine learning in general, will have a revolutionary potential to advance and synergize medical imaging and radiotherapy for unprecedented smart precision healthcare.

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