http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-114758783-A
Outgoing Links
| Predicate | Object |
|---|---|
| assignee | http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_caacf483b6be9ae2d2677103a70559db |
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-045 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-084 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T17-20 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H50-50 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-08 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H50-50 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-04 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T17-20 |
| filingDate | 2022-03-31-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor | http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_7fcb27b20827aff3df63ad920ea445f1 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_2ab87b985c084f64d20e834511a917c5 |
| publicationDate | 2022-07-15-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-114758783-A |
| titleOfInvention | Elastography method, apparatus, computer equipment and storage medium for deep learning |
| abstract | Embodiments of the present invention disclose a deep learning elastography method, device, computer equipment and storage medium. The method includes: establishing a correspondence between a tissue displacement field and a material distribution field as a training data set; building a conditional generative confrontation Network model; use the training data set to train the conditional generative adversarial network model, and train the conditional generative adversarial network model after training suitable for different conditions; use the measured displacement of the actual tissue as the input of the trained conditional generative adversarial network model , to obtain the material parameter distribution image of the actual tissue. The invention realizes the inversion of the material parameter distribution of the actual tissue based on the conditional generation confrontation network model, which can improve the calculation efficiency and the noise robustness. |
| isCitedBy | http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-115541030-A |
| priorityDate | 2022-03-31-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
| Predicate | Subject |
|---|---|
| isDiscussedBy | http://rdf.ncbi.nlm.nih.gov/pubchem/compound/CID24404 http://rdf.ncbi.nlm.nih.gov/pubchem/substance/SID419559532 |
Total number of triples: 21.