| Predicate |
Object |
| assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_f58ad95783942a842ee877a92e5b4096 |
| classificationCPCAdditional |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B6-032
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B6-037
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20084
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-10104
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20081
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-10081
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-30016
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-10088
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B5-055 |
| classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B6-5247
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-0016
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B6-5235
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H50-20
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H30-40 |
| classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G01T1-161
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/A61B5-055
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/A61B5-00 |
| filingDate |
2019-09-12-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_c6c2b485f4673476b20046c8a0668505
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_8caa78a78934f6e1b98c5c07ffb3a689
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_7064bb6e28e87eb28dbe6295213a5370 |
| publicationDate |
2020-03-19-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber |
WO-2020054803-A1 |
| titleOfInvention |
Diagnosis assistance system and method |
| abstract |
In this invention, a system (10) for providing diagnosis assistance information (110) regarding the sickness of a patient (5) comprises: an acquisition unit (11) that acquires patient information (105) including actual image data (15) from an MR image of the patient, which contains at least a reference region containing a portion that includes an evaluation region; and an information provision unit (12) that provides diagnosis assistance information (110) based on pseudo-PET image data (115) of the evaluation region, which is generated from actual image data of patient-specific MR images by an image processing model (60). The image processing model (60) is built by machine learning on the basis of training data (70) comprising, from a plurality of test subjects, actual image data (71) of MR images of the reference region and actual image data (72) of PET images containing the evaluation region, so as to generate pseudo-PET image data (75) of an evaluation region from actual image data (71) of a reference region MR image. |
| isCitedBy |
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/WO-2022065061-A1
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/WO-2022168969-A1
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/WO-2023167157-A1
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/WO-2022054711-A1 |
| priorityDate |
2018-09-12-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type |
http://data.epo.org/linked-data/def/patent/Publication |