| Predicate |
Object |
| assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_ac112bfbe3d0589e0e62dfa6d2209cfb |
| 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/G06T2200-08
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2200-04
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-30048
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-30101 |
| classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B6-504
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H50-50
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-08
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H50-20
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B6-507
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T15-08
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N20-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B6-481
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-0012
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B6-5217 |
| classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H50-50
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H50-20 |
| filingDate |
2019-04-10-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_2e15629565b55ab8ec9233d7ab7ff712
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_7ed30a76b506e5c4796e94a504c76c09
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_74819872c84fdfcd21fa9f4fcefa33d5 |
| publicationDate |
2021-02-17-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber |
EP-3776588-A1 |
| titleOfInvention |
Method and system for assessing vessel obstruction based on machine learning |
| abstract |
Methods and systems are described for assessing a vessel obstruction. The methods and systems obtain a volumetric image dataset for a target organ that includes a vessel of interest, extract an axial trajectory extending along of a vessel of interest (VOI) within the volumetric image dataset, and create a three-dimensional (3D) multi-planer reformatted (MPR) image based on the volumetric image dataset and the axial trajectory of the VOI. The methods and systems also extract a VOI parameter from the MPR utilizing a machine learning-based vessel obstruction assessment (VOA) model. Methods and systems are also described for implementing a prediction phase to perform at least one of i) detecting plaque type, ii) classifying anatomical severity of vessel blockage, and/or iii) classifying a hemodynamic severity of vessel obstructions within an unseen portion of the volumetric image data set. |
| priorityDate |
2018-04-11-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type |
http://data.epo.org/linked-data/def/patent/Publication |