| Predicate |
Object |
| assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_cbffa3b81b3b862dc7220b5648f5f745
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_8d0fc2b70675ee19bd5fc464f5ae9061 |
| classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B5-7275
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B5-7264
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H50-50
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B5-02007
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H50-20
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B5-0066
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B5-0071
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H30-40
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B5-0035
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B5-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B5-02 |
| classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H30-40
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H50-50
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H50-20
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/A61B5-02
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/A61B5-00 |
| filingDate |
2022-03-28-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_f5703f42a398a7fceafb19c4570f1bfa
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_c15bc932b88492a88f66bcebc98b51d2
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_e8d52ec76aa4561282270bfbce2e88b6
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_7501a8d79e227b3d1f6a69f1616eaab3 |
| publicationDate |
2022-10-06-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber |
WO-2022211402-A1 |
| titleOfInvention |
Atherosclerotic plaque tissue analysis method and device using multi-modal fusion image |
| abstract |
An operation method for an analysis device operated by means of at least one processor comprises the steps of: receiving a fusion image; and classifying tissue components of the fusion image by using an artificial intelligence model. The fusion image includes first information acquired by imaging a vascular tissue through an optical coherence tomography device, and second information acquired by imaging the vascular tissue through a fluorescence lifetime imaging device. The artificial intelligence model is a model trained to classify the tissue components by using morphological features and fluorescence lifetime image information included in the input image. |
| isCitedBy |
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-116486403-A
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-116486403-B |
| priorityDate |
2021-03-30-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type |
http://data.epo.org/linked-data/def/patent/Publication |