| Predicate |
Object |
| assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_971bb04e0fbc860061c8ac93ff64ed5a |
| classificationCPCAdditional |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20084
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20081
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-30096
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-30068
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-10116 |
| classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B6-502
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B6-48
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B6-481
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-045
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B6-5258
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-048
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-08
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-10
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-241 |
| classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-04
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/A61B6-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-08
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-62
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-10 |
| filingDate |
2021-06-09-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_460a232962c3c027d4c5afb8ce7c35b6 |
| publicationDate |
2021-08-24-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber |
CN-113288186-A |
| titleOfInvention |
Breast tumor tissue detection method and device based on deep learning algorithm |
| abstract |
The invention relates to a breast tumor tissue detection method and device based on a deep learning algorithm, wherein the method comprises: collecting images of existing confirmed cases, establishing a deep learning model for automatic detection of breast tumor tissue based on the existing images of confirmed cases, extracting or collecting images to be detected The case images are input to the deep learning model to obtain automatic detection results and calculate the change rate of blood perfusion in the lesions. Through the breast tumor tissue detection method and device based on the deep learning algorithm, the present invention significantly improves the detection rate of breast tumor tissue, and can realize accurate judgment and classification of benign and malignant breast lesions; through low-energy images and high-low energy subtraction images Combined method, contrast-enhanced energy spectrum mammography makes up for the lack of single low-energy image detection; combined with blood perfusion change rate and lesion tissue classification, it improves the ability to distinguish benign from malignant, and it is not easy to detect false negatives and false positives. . |
| isCitedBy |
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-114049934-A |
| priorityDate |
2021-06-09-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type |
http://data.epo.org/linked-data/def/patent/Publication |