http://rdf.ncbi.nlm.nih.gov/pubchem/reference/33911194

Outgoing Links

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contentType Journal Article
issn 1526-9914
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pageRange e13631-
publicationName Journal of Applied Clinical Medical Physics
startingPage e13631
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bibliographicCitation Xiao C, Jin J, Yi J, Han C, Zhou Y, Ai Y, Xie C, Jin X. RefineNet-based 2D and 3D automatic segmentations for clinical target volume and organs at risks for patients with cervical cancer in postoperative radiotherapy. J Appl Clin Med Phys. 2022 Jul;23(7):e13631. PMID: 35533205; PMCID: PMC9278674.
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date 2022-05-09^^<http://www.w3.org/2001/XMLSchema#date>
identifier https://pubmed.ncbi.nlm.nih.gov/35533205
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language English
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title RefineNet‐based 2D and 3D automatic segmentations for clinical target volume and organs at risks for patients with cervical cancer in postoperative radiotherapy
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