http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-111161272-B
Outgoing Links
| Predicate | Object |
|---|---|
| classificationCPCAdditional | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-30204 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-30044 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20221 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20084 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20081 |
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-10 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-10 |
| filingDate | 2019-12-31-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| grantDate | 2022-02-08-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationDate | 2022-02-08-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-111161272-B |
| titleOfInvention | Embryo tissue segmentation method based on generation of confrontation network |
| abstract | The invention relates to an embryonic tissue segmentation method based on a generation countermeasure network, and belongs to the technical field of medical image processing. The method comprises the following steps: step 1, performing tissue segmentation mask mapping on an embryo tissue slice image through a U-net network; step 2, making a segmentation network training set; step 3, configuring parameters required by network training to obtain a set network; step 4, using the tissue quality recognition network after the training setting of the manufactured segmentation network training set; step 5, fixing the parameters of the tissue quality recognition network, and using the manufactured segmentation network training set combined with the U-net network set by the tissue quality recognition network training; and 6, taking the embryonic tissue slice image without the marked segmentation result as input to generate a corresponding mask image. The segmentation method depends on that a classification model is used for compensating loss during training and segmentation of the network, so that the information of the cell growth state is fully utilized, and the accuracy of the segmentation network in the field of embryo tissue segmentation is improved. |
| priorityDate | 2019-12-31-04:00^^<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/substance/SID419701332 http://rdf.ncbi.nlm.nih.gov/pubchem/compound/CID22978774 |
Total number of triples: 17.