http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-104574456-B
Outgoing Links
| Predicate | Object |
|---|---|
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T11-00 |
| filingDate | 2014-12-01-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| grantDate | 2018-02-23-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationDate | 2018-02-23-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-104574456-B |
| titleOfInvention | A kind of super lack sampling K data imaging method of magnetic resonance based on figure regularization sparse coding |
| abstract | A kind of super lack sampling K data imaging method of magnetic resonance based on figure regularization sparse coding, comprises the following steps：(a)：The expression of figure regularization sparse coding is carried out on the graceful iteration framework of double-deck Burger, obtains image sparse model；(b)：Introduce auxiliary variable and the technology of rotation solution, renewal learning dictionary and sparse coefficient in the internal layer iteration of the graceful iteration of double-deck Burger；(c)：Constrained using the K data of the super lack sampling in part, image update is carried out in the external iteration of the graceful iteration of double-deck Burger, to obtain imaging results.The present invention learns to introduce figure regularization sparse coding method by self-adapting dictionary, establishes neighborhood graph to encode partial structurtes data and excavate its constraint in terms of geometric data so that view data can more preferable rarefaction representation；The other present invention can handle the more complicated image of local geometric features, can effectively capture local picture structure, recover more image details, obtained image result has more preferable fidelity. |
| priorityDate | 2014-12-01-04:00^^<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/compound/CID25572 http://rdf.ncbi.nlm.nih.gov/pubchem/substance/SID415713197 |
Total number of triples: 11.