http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-110189302-A
Outgoing Links
| Predicate | Object |
|---|---|
| assignee | http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_671c8f9e045c7595860c53744873750b |
| 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/G06T2207-10088 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-30016 |
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H30-20 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-241 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-0012 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-00 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-62 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H30-20 |
| filingDate | 2019-05-07-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor | http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_d363ae1094875f50d80fe9f3381bb833 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_6a5b9750cd509682f766247a7506a4ed http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_bee6cd073b62e5643ea14c52c9e09570 |
| publicationDate | 2019-08-30-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-110189302-A |
| titleOfInvention | Brain image analysis method, computer equipment and readable storage medium |
| abstract | The invention relates to a brain image analysis method, computer equipment and a readable storage medium. The method includes: receiving a brain structure image, extracting feature information of each brain region from the brain structure image as a node feature; The functional connection information of each brain interval is extracted from the functional image as the connection between nodes; the node characteristics and the connection between nodes are constructed into a graph characteristic matrix; the graph characteristic matrix is input into the training model to obtain the analysis results, where the training model is the sample brain The sample graph feature matrix constructed from structural images and sample brain functional images is input to the model trained in the graph network. In this method, since the input map characteristic matrix contains the characteristic information of each brain region in the brain structure image and the functional connection information of each brain region in the brain function image, it can reflect the brain image information more comprehensively and accurately; in addition, the training model can Quickly analyze the graph characteristic matrix, which improves the analysis efficiency of the graph characteristic matrix. |
| isCitedBy | http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-112948694-A http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-112948694-B http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-110720906-A http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-110720906-B http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-110852367-A http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-113080847-A |
| priorityDate | 2019-05-07-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
Total number of triples: 30.