Matches in SemOpenAlex for { <https://semopenalex.org/work/W4220882811> ?p ?o ?g. }
- W4220882811 endingPage "530" @default.
- W4220882811 startingPage "524" @default.
- W4220882811 abstract "Aims Microscopic examination is a basic diagnostic technology for colorectal cancer (CRC), but it is very laborious. We developed a dual resolution deep learning network with self-attention mechanism (DRSANet) which combines context and details for CRC binary classification and localisation in whole slide images (WSIs), and as a computer-aided diagnosis (CAD) to improve the sensitivity and specificity of doctors’ diagnosis. Methods Representative regions of interest (ROI) of each tissue type were manually delineated in WSIs by pathologists. Based on the same coordinates of centre position, patches were extracted at different magnification levels from the ROI. Specifically, patches from low magnification level contain contextual information, while from high magnification level provide important details. A dual-inputs network was designed to learn context and details simultaneously, and self-attention mechanism was used to selectively learn different positions in the images to enhance the performance. Results In classification task, DRSANet outperformed the benchmark networks which only depended on the high magnification patches on two test set. Furthermore, in localisation task, DRSANet demonstrated a better localisation capability of tumour area in WSI with less areas of misidentification. Conclusions We compared DRSANet with benchmark networks which only use the patches from high magnification level. Experimental results reveal that the performance of DRSANet is better than the benchmark networks. Both context and details should be considered in deep learning method." @default.
- W4220882811 created "2022-04-03" @default.
- W4220882811 creator A5028490514 @default.
- W4220882811 creator A5049963748 @default.
- W4220882811 creator A5066074514 @default.
- W4220882811 creator A5083164944 @default.
- W4220882811 creator A5086942701 @default.
- W4220882811 date "2022-03-10" @default.
- W4220882811 modified "2023-09-27" @default.
- W4220882811 title "Dual resolution deep learning network with self-attention mechanism for classification and localisation of colorectal cancer in histopathological images" @default.
- W4220882811 cites W2132162500 @default.
- W4220882811 cites W2183341477 @default.
- W4220882811 cites W2549976854 @default.
- W4220882811 cites W2752782242 @default.
- W4220882811 cites W2884585870 @default.
- W4220882811 cites W2888716711 @default.
- W4220882811 cites W2909082165 @default.
- W4220882811 cites W2914568698 @default.
- W4220882811 cites W2941707966 @default.
- W4220882811 cites W2949306187 @default.
- W4220882811 cites W2955058313 @default.
- W4220882811 cites W2956228567 @default.
- W4220882811 cites W2962858109 @default.
- W4220882811 cites W2969278648 @default.
- W4220882811 cites W2981689412 @default.
- W4220882811 cites W3017153481 @default.
- W4220882811 cites W3027822932 @default.
- W4220882811 cites W3027869849 @default.
- W4220882811 cites W3080854745 @default.
- W4220882811 cites W3089090082 @default.
- W4220882811 cites W3093253397 @default.
- W4220882811 cites W3098394437 @default.
- W4220882811 cites W3100398151 @default.
- W4220882811 cites W3124177967 @default.
- W4220882811 cites W3128210037 @default.
- W4220882811 cites W3128646645 @default.
- W4220882811 cites W3130936001 @default.
- W4220882811 cites W3206263253 @default.
- W4220882811 doi "https://doi.org/10.1136/jclinpath-2021-208042" @default.
- W4220882811 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35273120" @default.
- W4220882811 hasPublicationYear "2022" @default.
- W4220882811 type Work @default.
- W4220882811 citedByCount "2" @default.
- W4220882811 countsByYear W42208828112022 @default.
- W4220882811 countsByYear W42208828112023 @default.
- W4220882811 crossrefType "journal-article" @default.
- W4220882811 hasAuthorship W4220882811A5028490514 @default.
- W4220882811 hasAuthorship W4220882811A5049963748 @default.
- W4220882811 hasAuthorship W4220882811A5066074514 @default.
- W4220882811 hasAuthorship W4220882811A5083164944 @default.
- W4220882811 hasAuthorship W4220882811A5086942701 @default.
- W4220882811 hasConcept C108583219 @default.
- W4220882811 hasConcept C119857082 @default.
- W4220882811 hasConcept C12267149 @default.
- W4220882811 hasConcept C151730666 @default.
- W4220882811 hasConcept C153180895 @default.
- W4220882811 hasConcept C154945302 @default.
- W4220882811 hasConcept C162324750 @default.
- W4220882811 hasConcept C185798385 @default.
- W4220882811 hasConcept C187736073 @default.
- W4220882811 hasConcept C205649164 @default.
- W4220882811 hasConcept C2779343474 @default.
- W4220882811 hasConcept C2780451532 @default.
- W4220882811 hasConcept C31972630 @default.
- W4220882811 hasConcept C41008148 @default.
- W4220882811 hasConcept C4144372 @default.
- W4220882811 hasConcept C58640448 @default.
- W4220882811 hasConcept C66905080 @default.
- W4220882811 hasConcept C86803240 @default.
- W4220882811 hasConceptScore W4220882811C108583219 @default.
- W4220882811 hasConceptScore W4220882811C119857082 @default.
- W4220882811 hasConceptScore W4220882811C12267149 @default.
- W4220882811 hasConceptScore W4220882811C151730666 @default.
- W4220882811 hasConceptScore W4220882811C153180895 @default.
- W4220882811 hasConceptScore W4220882811C154945302 @default.
- W4220882811 hasConceptScore W4220882811C162324750 @default.
- W4220882811 hasConceptScore W4220882811C185798385 @default.
- W4220882811 hasConceptScore W4220882811C187736073 @default.
- W4220882811 hasConceptScore W4220882811C205649164 @default.
- W4220882811 hasConceptScore W4220882811C2779343474 @default.
- W4220882811 hasConceptScore W4220882811C2780451532 @default.
- W4220882811 hasConceptScore W4220882811C31972630 @default.
- W4220882811 hasConceptScore W4220882811C41008148 @default.
- W4220882811 hasConceptScore W4220882811C4144372 @default.
- W4220882811 hasConceptScore W4220882811C58640448 @default.
- W4220882811 hasConceptScore W4220882811C66905080 @default.
- W4220882811 hasConceptScore W4220882811C86803240 @default.
- W4220882811 hasIssue "8" @default.
- W4220882811 hasLocation W42208828111 @default.
- W4220882811 hasLocation W42208828112 @default.
- W4220882811 hasOpenAccess W4220882811 @default.
- W4220882811 hasPrimaryLocation W42208828111 @default.
- W4220882811 hasRelatedWork W2139751930 @default.
- W4220882811 hasRelatedWork W3014300295 @default.
- W4220882811 hasRelatedWork W3164822677 @default.
- W4220882811 hasRelatedWork W4223943233 @default.
- W4220882811 hasRelatedWork W4225161397 @default.
- W4220882811 hasRelatedWork W4312200629 @default.