Matches in SemOpenAlex for { <https://semopenalex.org/work/W2753801833> ?p ?o ?g. }
Showing items 1 to 86 of
86
with 100 items per page.
- W2753801833 endingPage "664" @default.
- W2753801833 startingPage "656" @default.
- W2753801833 abstract "The classification of benign versus malignant lung nodules using chest CT plays a pivotal role in the early detection of lung cancer and this early detection has the best chance of cure. Although deep learning is now the most successful solution for image classification problems, it requires a myriad number of training data, which are not usually readily available for most routine medical imaging applications. In this paper, we propose the transferable multi-model ensemble (TMME) algorithm to separate malignant from benign lung nodules using limited chest CT data. This algorithm transfers the image representation abilities of three ResNet-50 models, which were pre-trained on the ImageNet database, to characterize the overall appearance, heterogeneity of voxel values and heterogeneity of shape of lung nodules, respectively, and jointly utilizes them to classify lung nodules with an adaptive weighting scheme learned during the error back propagation. Experimental results on the benchmark LIDC-IDRI dataset show that our proposed TMME algorithm achieves a lung nodule classification accuracy of 93.40%, which is markedly higher than the accuracy of seven state-of-the-art approaches." @default.
- W2753801833 created "2017-09-15" @default.
- W2753801833 creator A5011835422 @default.
- W2753801833 creator A5029102592 @default.
- W2753801833 creator A5034520275 @default.
- W2753801833 creator A5068891693 @default.
- W2753801833 creator A5076697411 @default.
- W2753801833 creator A5082979981 @default.
- W2753801833 date "2017-01-01" @default.
- W2753801833 modified "2023-10-03" @default.
- W2753801833 title "Transferable Multi-model Ensemble for Benign-Malignant Lung Nodule Classification on Chest CT" @default.
- W2753801833 cites W130099911 @default.
- W2753801833 cites W1916279783 @default.
- W2753801833 cites W1986649315 @default.
- W2753801833 cites W2078014989 @default.
- W2753801833 cites W2097117768 @default.
- W2753801833 cites W2120903075 @default.
- W2753801833 cites W2170552969 @default.
- W2753801833 cites W2194775991 @default.
- W2753801833 cites W2237167366 @default.
- W2753801833 cites W2394599079 @default.
- W2753801833 cites W2543630535 @default.
- W2753801833 cites W2560118069 @default.
- W2753801833 cites W2733946950 @default.
- W2753801833 cites W913555550 @default.
- W2753801833 doi "https://doi.org/10.1007/978-3-319-66179-7_75" @default.
- W2753801833 hasPublicationYear "2017" @default.
- W2753801833 type Work @default.
- W2753801833 sameAs 2753801833 @default.
- W2753801833 citedByCount "41" @default.
- W2753801833 countsByYear W27538018332018 @default.
- W2753801833 countsByYear W27538018332019 @default.
- W2753801833 countsByYear W27538018332020 @default.
- W2753801833 countsByYear W27538018332021 @default.
- W2753801833 countsByYear W27538018332022 @default.
- W2753801833 countsByYear W27538018332023 @default.
- W2753801833 crossrefType "book-chapter" @default.
- W2753801833 hasAuthorship W2753801833A5011835422 @default.
- W2753801833 hasAuthorship W2753801833A5029102592 @default.
- W2753801833 hasAuthorship W2753801833A5034520275 @default.
- W2753801833 hasAuthorship W2753801833A5068891693 @default.
- W2753801833 hasAuthorship W2753801833A5076697411 @default.
- W2753801833 hasAuthorship W2753801833A5082979981 @default.
- W2753801833 hasBestOaLocation W27538018332 @default.
- W2753801833 hasConcept C126322002 @default.
- W2753801833 hasConcept C126838900 @default.
- W2753801833 hasConcept C142724271 @default.
- W2753801833 hasConcept C151730666 @default.
- W2753801833 hasConcept C2776731575 @default.
- W2753801833 hasConcept C2777714996 @default.
- W2753801833 hasConcept C2780244788 @default.
- W2753801833 hasConcept C41008148 @default.
- W2753801833 hasConcept C544519230 @default.
- W2753801833 hasConcept C71924100 @default.
- W2753801833 hasConcept C86803240 @default.
- W2753801833 hasConceptScore W2753801833C126322002 @default.
- W2753801833 hasConceptScore W2753801833C126838900 @default.
- W2753801833 hasConceptScore W2753801833C142724271 @default.
- W2753801833 hasConceptScore W2753801833C151730666 @default.
- W2753801833 hasConceptScore W2753801833C2776731575 @default.
- W2753801833 hasConceptScore W2753801833C2777714996 @default.
- W2753801833 hasConceptScore W2753801833C2780244788 @default.
- W2753801833 hasConceptScore W2753801833C41008148 @default.
- W2753801833 hasConceptScore W2753801833C544519230 @default.
- W2753801833 hasConceptScore W2753801833C71924100 @default.
- W2753801833 hasConceptScore W2753801833C86803240 @default.
- W2753801833 hasLocation W27538018331 @default.
- W2753801833 hasLocation W27538018332 @default.
- W2753801833 hasOpenAccess W2753801833 @default.
- W2753801833 hasPrimaryLocation W27538018331 @default.
- W2753801833 hasRelatedWork W1980761243 @default.
- W2753801833 hasRelatedWork W2010920639 @default.
- W2753801833 hasRelatedWork W2043351610 @default.
- W2753801833 hasRelatedWork W2063957001 @default.
- W2753801833 hasRelatedWork W2158839023 @default.
- W2753801833 hasRelatedWork W2416760686 @default.
- W2753801833 hasRelatedWork W2470349069 @default.
- W2753801833 hasRelatedWork W2789892372 @default.
- W2753801833 hasRelatedWork W3113030889 @default.
- W2753801833 hasRelatedWork W3187267698 @default.
- W2753801833 isParatext "false" @default.
- W2753801833 isRetracted "false" @default.
- W2753801833 magId "2753801833" @default.
- W2753801833 workType "book-chapter" @default.