http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-112329871-B
Outgoing Links
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|---|---|
| classificationCPCAdditional | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06V2201-032 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20084 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-30064 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20081 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-10081 |
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-0012 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-045 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-213 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-2415 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-214 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06V10-774 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-62 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-00 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06V10-77 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-04 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06V10-82 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06V10-764 |
| filingDate | 2020-11-11-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| grantDate | 2022-03-08-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationDate | 2022-03-08-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-112329871-B |
| titleOfInvention | A method for lung nodule detection based on self-correcting convolution and channel attention mechanism |
| abstract | The invention discloses a lung nodule detection method based on self-correction convolution and channel attention mechanism. The detection method establishes a lung nodule detection network integrating a u-net-type encoder-decoder network, and the encoder gradually By reducing the spatial dimension of the pooling layer, the decoder gradually repairs the details and spatial dimensions of the object, and establishes skip connections between the encoder and the decoder to help the decoder better repair the details of the object. The value of the loss function consists of two parts: classification loss and regression loss, which solves the problem of imbalance in the ratio of positive samples to negative samples in the LUNA16 dataset. The detection method can have a good recognition effect on various pulmonary nodules of different scales and shapes, and can also accurately identify various false positive nodules, which improves the detection accuracy of pulmonary nodules in medical images, and can be used for The computer-aided diagnosis system solves the problem of difficult identification of pulmonary nodules of different scales and shapes. |
| priorityDate | 2020-11-11-04:00^^<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/CID962 http://rdf.ncbi.nlm.nih.gov/pubchem/substance/SID419512635 |
Total number of triples: 27.