Matches in SemOpenAlex for { <https://semopenalex.org/work/W2922405163> ?p ?o ?g. }
Showing items 1 to 92 of
92
with 100 items per page.
- W2922405163 abstract "We propose a method to automatically segment multiple organs at risk (OARs) from routinely-acquired thorax CT images using generative adversarial network (GAN). Multi-label U-Net was introduced in generator to enable end-to-end segmentation. Esophagus and spinal cord location information were used to train the GAN in specific regions of interest (ROI). The probability maps of new CT thorax multi-organ were generated by the well-trained network and fused to reconstruct the final contour. This proposed algorithm was evaluated using 20 patients' data with thorax CT images and manual contours. The mean Dice similarity coefficient (DSC) for esophagus, heart, left lung, right lung and spinal cord was 0.73±0.04, 0.85±0.02, 0.96±0.01, 0.97±0.02 and 0.88±0.03. This novel deep-learning-based approach with the GAN strategy can automatically and accurately segment multiple OARs in thorax CT images, which could be a useful tool to improve the efficiency of the lung radiotherapy treatment planning." @default.
- W2922405163 created "2019-03-22" @default.
- W2922405163 creator A5009731683 @default.
- W2922405163 creator A5011903902 @default.
- W2922405163 creator A5026088869 @default.
- W2922405163 creator A5029644534 @default.
- W2922405163 creator A5048786190 @default.
- W2922405163 creator A5049656223 @default.
- W2922405163 creator A5053851809 @default.
- W2922405163 creator A5059220012 @default.
- W2922405163 creator A5067547603 @default.
- W2922405163 creator A5072748292 @default.
- W2922405163 creator A5080256711 @default.
- W2922405163 creator A5083935587 @default.
- W2922405163 creator A5087306292 @default.
- W2922405163 date "2019-03-13" @default.
- W2922405163 modified "2023-10-05" @default.
- W2922405163 title "Automatic multi-organ segmentation in thorax CT images using U-Net-GAN" @default.
- W2922405163 cites W1667869507 @default.
- W2922405163 cites W1901606657 @default.
- W2922405163 cites W2012694467 @default.
- W2922405163 cites W2015874969 @default.
- W2922405163 cites W2036390026 @default.
- W2922405163 cites W2074271088 @default.
- W2922405163 cites W2080830831 @default.
- W2922405163 cites W2137013440 @default.
- W2922405163 cites W2162140684 @default.
- W2922405163 cites W2171963641 @default.
- W2922405163 cites W2555096873 @default.
- W2922405163 cites W2560725027 @default.
- W2922405163 cites W2778764040 @default.
- W2922405163 cites W2914533527 @default.
- W2922405163 cites W2962914239 @default.
- W2922405163 doi "https://doi.org/10.1117/12.2512552" @default.
- W2922405163 hasPublicationYear "2019" @default.
- W2922405163 type Work @default.
- W2922405163 sameAs 2922405163 @default.
- W2922405163 citedByCount "4" @default.
- W2922405163 countsByYear W29224051632020 @default.
- W2922405163 countsByYear W29224051632021 @default.
- W2922405163 countsByYear W29224051632022 @default.
- W2922405163 crossrefType "proceedings-article" @default.
- W2922405163 hasAuthorship W2922405163A5009731683 @default.
- W2922405163 hasAuthorship W2922405163A5011903902 @default.
- W2922405163 hasAuthorship W2922405163A5026088869 @default.
- W2922405163 hasAuthorship W2922405163A5029644534 @default.
- W2922405163 hasAuthorship W2922405163A5048786190 @default.
- W2922405163 hasAuthorship W2922405163A5049656223 @default.
- W2922405163 hasAuthorship W2922405163A5053851809 @default.
- W2922405163 hasAuthorship W2922405163A5059220012 @default.
- W2922405163 hasAuthorship W2922405163A5067547603 @default.
- W2922405163 hasAuthorship W2922405163A5072748292 @default.
- W2922405163 hasAuthorship W2922405163A5080256711 @default.
- W2922405163 hasAuthorship W2922405163A5083935587 @default.
- W2922405163 hasAuthorship W2922405163A5087306292 @default.
- W2922405163 hasConcept C105702510 @default.
- W2922405163 hasConcept C124504099 @default.
- W2922405163 hasConcept C153180895 @default.
- W2922405163 hasConcept C154945302 @default.
- W2922405163 hasConcept C163892561 @default.
- W2922405163 hasConcept C2777819096 @default.
- W2922405163 hasConcept C41008148 @default.
- W2922405163 hasConcept C71924100 @default.
- W2922405163 hasConcept C89600930 @default.
- W2922405163 hasConcept C97834683 @default.
- W2922405163 hasConceptScore W2922405163C105702510 @default.
- W2922405163 hasConceptScore W2922405163C124504099 @default.
- W2922405163 hasConceptScore W2922405163C153180895 @default.
- W2922405163 hasConceptScore W2922405163C154945302 @default.
- W2922405163 hasConceptScore W2922405163C163892561 @default.
- W2922405163 hasConceptScore W2922405163C2777819096 @default.
- W2922405163 hasConceptScore W2922405163C41008148 @default.
- W2922405163 hasConceptScore W2922405163C71924100 @default.
- W2922405163 hasConceptScore W2922405163C89600930 @default.
- W2922405163 hasConceptScore W2922405163C97834683 @default.
- W2922405163 hasLocation W29224051631 @default.
- W2922405163 hasOpenAccess W2922405163 @default.
- W2922405163 hasPrimaryLocation W29224051631 @default.
- W2922405163 hasRelatedWork W1502223807 @default.
- W2922405163 hasRelatedWork W1507687735 @default.
- W2922405163 hasRelatedWork W2015538044 @default.
- W2922405163 hasRelatedWork W2415731916 @default.
- W2922405163 hasRelatedWork W2564351535 @default.
- W2922405163 hasRelatedWork W2602477100 @default.
- W2922405163 hasRelatedWork W2769435486 @default.
- W2922405163 hasRelatedWork W4214881770 @default.
- W2922405163 hasRelatedWork W4221141253 @default.
- W2922405163 hasRelatedWork W4280550577 @default.
- W2922405163 isParatext "false" @default.
- W2922405163 isRetracted "false" @default.
- W2922405163 magId "2922405163" @default.
- W2922405163 workType "article" @default.