http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-2018336680-A1

Outgoing Links

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classificationCPCAdditional http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-30016
classificationCPCInventive http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B5-0042
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01R33-4806
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B5-055
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-0012
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01R33-20
classificationIPCInventive http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G01R33-20
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/A61B5-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/A61B5-055
filingDate 2018-05-18-04:00^^<http://www.w3.org/2001/XMLSchema#date>
inventor http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_9bef002c414ae3f4be3a4444047d8cef
publicationDate 2018-11-22-04:00^^<http://www.w3.org/2001/XMLSchema#date>
publicationNumber US-2018336680-A1
titleOfInvention Method and apparatus for functional magnetic resonance imaging
abstract An ICA to identify a large number of candidate correlation patterns is carried out based on a time series of image data. The large number of candidate correlation patterns includes a large number of neurophysical events, as well as false patterns owing to noise. The neurophysical events as well as the false patterns are then separated, for example on the basis of a metric, which indicates an intensity of the candidate correlation patterns in a section of the brain, or by a computer-implemented classifier. Techniques of this kind can be used in conjunction with functional magnetic resonance imaging.
isCitedBy http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-10859657-B2
priorityDate 2017-05-19-04:00^^<http://www.w3.org/2001/XMLSchema#date>
type http://data.epo.org/linked-data/def/patent/Publication

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Total number of triples: 23.