http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-2021224990-A1

Outgoing Links

Predicate Object
assignee http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_75b86e50a7529f6158517db14a0b81df
classificationCPCAdditional http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20036
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-30024
classificationCPCInventive http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-0012
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-0014
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-11
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-187
classificationIPCInventive http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-11
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-00
filingDate 2017-05-24-04:00^^<http://www.w3.org/2001/XMLSchema#date>
inventor http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_1a9fb51e87ca35594db867cf6a1ba418
publicationDate 2021-07-22-04:00^^<http://www.w3.org/2001/XMLSchema#date>
publicationNumber US-2021224990-A1
titleOfInvention Biological object detection
abstract As the capabilities of digital histopathology machines grows, there is an increasing need to ease the burden on pathology professionals of finding interesting structures in such images. Digital histopathology images can be at least several Gigabytes in size, and they may contain millions of cell structures of interest. Automated algorithms for finding structures in such images have been proposed, such as the Active Contour Model (ACM). The ACM algorithm can have difficulty detecting regions in images having variable colour or texture distributions. Such regions are often found in images containing cell nuclei, because nuclei do not always have a homogeneous appearance. The present application describes a technique to identify inhomogeneous structures, for example, cell nuclei, in digital histopathology information. It is proposed to search pre-computed super-pixel information using a morphological variable, such as a shape-compactness metric, to identify candidate objects.
isCitedBy http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-11417130-B2
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-2020380319-A1
priorityDate 2016-06-03-04:00^^<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/CID442514
http://rdf.ncbi.nlm.nih.gov/pubchem/substance/SID419581356

Total number of triples: 22.