http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-109671060-B
Outgoing Links
| Predicate | Object |
|---|---|
| classificationCPCAdditional | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-10081 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20101 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-30068 |
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-11 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-0012 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H50-20 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-187 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-08 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-045 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H30-20 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H30-20 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-187 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H50-20 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-11 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-04 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-00 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-08 |
| filingDate | 2018-12-06-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| grantDate | 2021-12-17-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationDate | 2021-12-17-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-109671060-B |
| titleOfInvention | Computer-aided breast mass detection method based on selective search and CNN |
| abstract | The invention proposes a computer-aided breast mass detection method based on selective search and CNN, which is used to solve the technical problem of low detection accuracy caused by poor candidate frame quality and low classification accuracy in the prior art. The steps are: 1. Acquiring multiple mammography X-ray images and their physician's annotation files; 2. Preprocessing N mammography X-ray images; 3. Obtaining N preprocessed mammography X-ray images 4. Obtain the candidate frame set of N preprocessed mammography images based on the selective search algorithm; 5. Construct a convolutional neural network CNN and initialize it; 6. Analyze the initialized convolutional neural network The network is trained; 7. Obtain the mass area of the mammography image to be detected. The breast mass detection method of the invention has high detection rate and low false positive rate, and can be applied to a computer-aided breast mass detection system. |
| priorityDate | 2018-12-06-04:00^^<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/CID23932 http://rdf.ncbi.nlm.nih.gov/pubchem/substance/SID419405613 |
Total number of triples: 27.