http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-108986114-B
Outgoing Links
| Predicate | Object |
|---|---|
| classificationCPCAdditional | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-30056 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-10016 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-10081 |
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-11 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-11 |
| filingDate | 2018-07-11-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| grantDate | 2022-03-29-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationDate | 2022-03-29-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-108986114-B |
| titleOfInvention | An automatic liver segmentation method for abdominal CT sequence images based on level set and shape descriptor |
| abstract | The invention discloses an automatic liver segmentation method for abdominal CT sequence images based on level sets and shape descriptors, comprising: preprocessing input images to remove irrelevant organs and tissues; The correlation between adjacent slices of the sequence constructs a level set energy function. Taking the initial slice as the starting point, an iterative strategy is used to complete the automatic liver segmentation of abdominal CT sequence images; local and global shape descriptors are constructed to remove over-segmented regions and optimize liver edges. The method of the invention can effectively segment the liver region in the abdominal CT sequence image which is seriously polluted by noise and has grayscale heterogeneity, can effectively avoid the mis-segmentation of adjacent tissues around the liver, remove the over-segmented region caused by grayscale overlap, and improve the Liver segmentation accuracy. |
| priorityDate | 2018-07-11-04:00^^<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: 15.