Matches in SemOpenAlex for { <https://semopenalex.org/work/W2992438939> ?p ?o ?g. }
- W2992438939 abstract "Training convolutional neural networks (CNNs) for medical image segmentation often requires large and representative sets of images and their corresponding annotations. Obtaining annotated images usually requires manual intervention, which is expensive and time consuming, as it typically requires a specialist. An alternative approach is to leverage existing automatic segmentation tools and combine them to create consensus-based annotations. A drawback to this approach is that silver-standards are usually smooth and this smoothness is transmitted to the output segmentation of the network. Our proposal is to use a two-staged approach. First, silver-standard datasets are used to generate a large set of annotated images in order to train the brain extraction network from scratch. Second, fine-tuning is performed using much smaller amounts of manually annotated data so that the network can learn the finer details that are not preserved in the silver-standard data. As an example, our two-staged brain extraction approach has been shown to outperform seven state-of-the-art techniques across three different public datasets. Our results also suggest that CNNs can potentially capture inter-rater annotation variability between experts who annotate the same set of images following the same guidelines, and also adapt to different annotation guidelines." @default.
- W2992438939 created "2019-12-13" @default.
- W2992438939 creator A5012558108 @default.
- W2992438939 creator A5017698959 @default.
- W2992438939 creator A5034139388 @default.
- W2992438939 creator A5035088462 @default.
- W2992438939 creator A5083770219 @default.
- W2992438939 creator A5085398611 @default.
- W2992438939 creator A5087970571 @default.
- W2992438939 creator A5088481433 @default.
- W2992438939 date "2019-10-01" @default.
- W2992438939 modified "2023-10-09" @default.
- W2992438939 title "Brain Extraction Network Trained with Silver Standard Data and Fine-Tuned with Manual Annotation for Improved Segmentation" @default.
- W2992438939 cites W1484720787 @default.
- W2992438939 cites W1576648105 @default.
- W2992438939 cites W1901129140 @default.
- W2992438939 cites W2071881327 @default.
- W2992438939 cites W2083099567 @default.
- W2992438939 cites W2085641953 @default.
- W2992438939 cites W2127890285 @default.
- W2992438939 cites W2136145485 @default.
- W2992438939 cites W2138197318 @default.
- W2992438939 cites W2145661921 @default.
- W2992438939 cites W2148347694 @default.
- W2992438939 cites W2150534249 @default.
- W2992438939 cites W2151050383 @default.
- W2992438939 cites W2151721316 @default.
- W2992438939 cites W2157270343 @default.
- W2992438939 cites W2284198383 @default.
- W2992438939 cites W2602865573 @default.
- W2992438939 cites W2611775752 @default.
- W2992438939 cites W2729876886 @default.
- W2992438939 cites W2742774307 @default.
- W2992438939 cites W2767301142 @default.
- W2992438939 cites W2794613614 @default.
- W2992438939 cites W2806077272 @default.
- W2992438939 cites W2962930554 @default.
- W2992438939 cites W2964121744 @default.
- W2992438939 cites W2964156854 @default.
- W2992438939 cites W1857789879 @default.
- W2992438939 doi "https://doi.org/10.1109/sibgrapi.2019.00039" @default.
- W2992438939 hasPublicationYear "2019" @default.
- W2992438939 type Work @default.
- W2992438939 sameAs 2992438939 @default.
- W2992438939 citedByCount "0" @default.
- W2992438939 crossrefType "proceedings-article" @default.
- W2992438939 hasAuthorship W2992438939A5012558108 @default.
- W2992438939 hasAuthorship W2992438939A5017698959 @default.
- W2992438939 hasAuthorship W2992438939A5034139388 @default.
- W2992438939 hasAuthorship W2992438939A5035088462 @default.
- W2992438939 hasAuthorship W2992438939A5083770219 @default.
- W2992438939 hasAuthorship W2992438939A5085398611 @default.
- W2992438939 hasAuthorship W2992438939A5087970571 @default.
- W2992438939 hasAuthorship W2992438939A5088481433 @default.
- W2992438939 hasConcept C108583219 @default.
- W2992438939 hasConcept C124101348 @default.
- W2992438939 hasConcept C124504099 @default.
- W2992438939 hasConcept C153083717 @default.
- W2992438939 hasConcept C153180895 @default.
- W2992438939 hasConcept C154945302 @default.
- W2992438939 hasConcept C177264268 @default.
- W2992438939 hasConcept C199360897 @default.
- W2992438939 hasConcept C2776321320 @default.
- W2992438939 hasConcept C41008148 @default.
- W2992438939 hasConcept C50644808 @default.
- W2992438939 hasConcept C52622490 @default.
- W2992438939 hasConcept C58489278 @default.
- W2992438939 hasConcept C81363708 @default.
- W2992438939 hasConcept C89600930 @default.
- W2992438939 hasConceptScore W2992438939C108583219 @default.
- W2992438939 hasConceptScore W2992438939C124101348 @default.
- W2992438939 hasConceptScore W2992438939C124504099 @default.
- W2992438939 hasConceptScore W2992438939C153083717 @default.
- W2992438939 hasConceptScore W2992438939C153180895 @default.
- W2992438939 hasConceptScore W2992438939C154945302 @default.
- W2992438939 hasConceptScore W2992438939C177264268 @default.
- W2992438939 hasConceptScore W2992438939C199360897 @default.
- W2992438939 hasConceptScore W2992438939C2776321320 @default.
- W2992438939 hasConceptScore W2992438939C41008148 @default.
- W2992438939 hasConceptScore W2992438939C50644808 @default.
- W2992438939 hasConceptScore W2992438939C52622490 @default.
- W2992438939 hasConceptScore W2992438939C58489278 @default.
- W2992438939 hasConceptScore W2992438939C81363708 @default.
- W2992438939 hasConceptScore W2992438939C89600930 @default.
- W2992438939 hasLocation W29924389391 @default.
- W2992438939 hasOpenAccess W2992438939 @default.
- W2992438939 hasPrimaryLocation W29924389391 @default.
- W2992438939 hasRelatedWork W1558571355 @default.
- W2992438939 hasRelatedWork W2616788541 @default.
- W2992438939 hasRelatedWork W2743554749 @default.
- W2992438939 hasRelatedWork W2901422868 @default.
- W2992438939 hasRelatedWork W2909712455 @default.
- W2992438939 hasRelatedWork W2949795898 @default.
- W2992438939 hasRelatedWork W2980201311 @default.
- W2992438939 hasRelatedWork W2981519241 @default.
- W2992438939 hasRelatedWork W3005763828 @default.
- W2992438939 hasRelatedWork W3009946637 @default.
- W2992438939 hasRelatedWork W3039531091 @default.
- W2992438939 hasRelatedWork W3103717993 @default.
- W2992438939 hasRelatedWork W3105039763 @default.