http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-113240680-A

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filingDate 2021-05-18-04:00^^<http://www.w3.org/2001/XMLSchema#date>
inventor http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_cb2fe504a87eb43f62e968d0dff09f37
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publicationDate 2021-08-10-04:00^^<http://www.w3.org/2001/XMLSchema#date>
publicationNumber CN-113240680-A
titleOfInvention Automatic colorectal cancer mesentery segmentation method based on deep learning technology
abstract The invention discloses a rectal cancer mesentery automatic segmentation method based on a deep learning technology, which specifically comprises the following steps: the method comprises the following steps: acquiring a rectal cancer T2 image; step two: manual labeling of the rectal cancer mesentery of each patient; step three: preprocessing an original image and an annotation Result (ROI); step four: training and testing a model; step five: training and testing result display; compared with a manual marking method, the method provided by the invention has the advantages that the manual intervention is reduced, the lesion identification efficiency is greatly improved, and the accuracy is also improved.
isCitedBy http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-115170568-A
priorityDate 2021-05-18-04:00^^<http://www.w3.org/2001/XMLSchema#date>
type http://data.epo.org/linked-data/def/patent/Publication

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Total number of triples: 23.