http://rdf.ncbi.nlm.nih.gov/pubchem/patent/WO-2019025298-A1
Outgoing Links
| Predicate | Object |
|---|---|
| assignee | http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_ca32fd2a44fd326ffd027a75a57bd13f |
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-08 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T3-4069 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T3-4053 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T3-4076 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T3-40 |
| filingDate | 2018-07-26-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor | http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_44c6c01166d916826b510f4115453466 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_e05f3b300e450cb0273ac35e07745f4a |
| publicationDate | 2019-02-07-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | WO-2019025298-A1 |
| titleOfInvention | METHOD, DEVICE AND COMPUTER PROGRAM FOR IMPROVING THE RECONSTRUCTION OF VERY HIGH RESOLUTION DENSED IMAGES FROM LIMITED-LIFE DIFFRACTION IMAGES ACQUIRED BY MONOMOLECULAR LOCATION MICROSCOPY |
| abstract | The invention relates to the reconstruction of a very high resolution dense synthetic image from at least one low information content image, for example from a limited diffraction image sequence, acquired by microscopy of monomolecular localization. After obtaining such a limited diffraction image sequence, a sparse localization image is reconstructed from the obtained limited diffraction image sequence according to a monomolecular localization microscopy image processing. The reconstructed sparse localization image and / or a corresponding low resolution wide field image are entered into an artificial neural network and a very high resolution dense synthetic image is obtained from the artificial neural network, the latter being formed at the same time. using training data comprising scattered location image triplets, at least partially corresponding low resolution wide field images, and corresponding very high resolution dense images as a function of an objective function of learning comparing dense images at very high resolution and corresponding outputs of the artificial neural network. |
| isCitedBy | http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-2022206469-A1 http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-11164721-B2 http://rdf.ncbi.nlm.nih.gov/pubchem/patent/WO-2022064763-A1 http://rdf.ncbi.nlm.nih.gov/pubchem/patent/JP-7346726-B2 http://rdf.ncbi.nlm.nih.gov/pubchem/patent/WO-2020198752-A1 http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-110084745-A http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-11557459-B2 http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-110648293-B http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-110751597-A http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-110648293-A |
| priorityDate | 2017-07-31-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
Total number of triples: 41.