Matches in SemOpenAlex for { <https://semopenalex.org/work/W3165855571> ?p ?o ?g. }
Showing items 1 to 87 of
87
with 100 items per page.
- W3165855571 abstract "Colorectal Cancer (CRC) is a leading cause of death around the globe, and therefore, the analysis of tumor micro environment in the CRC WSIs is important for the early detection of CRC. Conventional visual inspection is very time consuming and the process can undergo inaccuracies because of the subject-level assessment. Deep learning has shown promising results in medical image analysis. However, these approaches require a lot of labeling images from medical experts. In this paper, we propose a semi-supervised algorithm for CRC tissue classification. We propose to employ the hypergraph neural network to classify seven different biologically meaningful CRC tissue types. Firstly, image deep features are extracted from input patches using the pre-trained VGG19 model. The hypergraph is then constructed whereby patch-level deep features represent the vertices of hypergraph and hyperedges are assigned using pair-wise euclidean distance. The edges, vertices, and their corresponding patch-level features are passed through a feed-forward neural network to perform tissue classification in a transductive manner. Experiments are performed on an independent CRC tissue classification dataset and compared with existing state-of-the-art methods. Our results reveal that the proposed algorithm outperforms existing methods by achieving an overall accuracy of 95.46% and AvTP of 94.42%." @default.
- W3165855571 created "2021-06-07" @default.
- W3165855571 creator A5028846094 @default.
- W3165855571 creator A5035672070 @default.
- W3165855571 creator A5056682970 @default.
- W3165855571 creator A5059512412 @default.
- W3165855571 creator A5071515463 @default.
- W3165855571 date "2021-04-13" @default.
- W3165855571 modified "2023-10-15" @default.
- W3165855571 title "Colorectal Cancer Tissue Classification Using Semi-Supervised Hypergraph Convolutional Network" @default.
- W3165855571 cites W1988445395 @default.
- W3165855571 cites W2025268894 @default.
- W3165855571 cites W2037696125 @default.
- W3165855571 cites W2041538370 @default.
- W3165855571 cites W2123556341 @default.
- W3165855571 cites W2168593098 @default.
- W3165855571 cites W2194775991 @default.
- W3165855571 cites W2282915343 @default.
- W3165855571 cites W2294205003 @default.
- W3165855571 cites W2435090885 @default.
- W3165855571 cites W2562005596 @default.
- W3165855571 cites W2566972569 @default.
- W3165855571 cites W2593068728 @default.
- W3165855571 cites W2638507138 @default.
- W3165855571 cites W2766865858 @default.
- W3165855571 cites W2790824977 @default.
- W3165855571 cites W2890197544 @default.
- W3165855571 cites W2902977244 @default.
- W3165855571 cites W2914568698 @default.
- W3165855571 cites W2923287877 @default.
- W3165855571 cites W2963446712 @default.
- W3165855571 cites W3089265920 @default.
- W3165855571 doi "https://doi.org/10.1109/isbi48211.2021.9434036" @default.
- W3165855571 hasPublicationYear "2021" @default.
- W3165855571 type Work @default.
- W3165855571 sameAs 3165855571 @default.
- W3165855571 citedByCount "4" @default.
- W3165855571 countsByYear W31658555712022 @default.
- W3165855571 countsByYear W31658555712023 @default.
- W3165855571 crossrefType "proceedings-article" @default.
- W3165855571 hasAuthorship W3165855571A5028846094 @default.
- W3165855571 hasAuthorship W3165855571A5035672070 @default.
- W3165855571 hasAuthorship W3165855571A5056682970 @default.
- W3165855571 hasAuthorship W3165855571A5059512412 @default.
- W3165855571 hasAuthorship W3165855571A5071515463 @default.
- W3165855571 hasConcept C108583219 @default.
- W3165855571 hasConcept C111919701 @default.
- W3165855571 hasConcept C118615104 @default.
- W3165855571 hasConcept C119857082 @default.
- W3165855571 hasConcept C153180895 @default.
- W3165855571 hasConcept C154945302 @default.
- W3165855571 hasConcept C2781221856 @default.
- W3165855571 hasConcept C33923547 @default.
- W3165855571 hasConcept C41008148 @default.
- W3165855571 hasConcept C50644808 @default.
- W3165855571 hasConcept C81363708 @default.
- W3165855571 hasConcept C98045186 @default.
- W3165855571 hasConceptScore W3165855571C108583219 @default.
- W3165855571 hasConceptScore W3165855571C111919701 @default.
- W3165855571 hasConceptScore W3165855571C118615104 @default.
- W3165855571 hasConceptScore W3165855571C119857082 @default.
- W3165855571 hasConceptScore W3165855571C153180895 @default.
- W3165855571 hasConceptScore W3165855571C154945302 @default.
- W3165855571 hasConceptScore W3165855571C2781221856 @default.
- W3165855571 hasConceptScore W3165855571C33923547 @default.
- W3165855571 hasConceptScore W3165855571C41008148 @default.
- W3165855571 hasConceptScore W3165855571C50644808 @default.
- W3165855571 hasConceptScore W3165855571C81363708 @default.
- W3165855571 hasConceptScore W3165855571C98045186 @default.
- W3165855571 hasFunder F4320321386 @default.
- W3165855571 hasLocation W31658555711 @default.
- W3165855571 hasOpenAccess W3165855571 @default.
- W3165855571 hasPrimaryLocation W31658555711 @default.
- W3165855571 hasRelatedWork W3029198973 @default.
- W3165855571 hasRelatedWork W3133861977 @default.
- W3165855571 hasRelatedWork W3138003926 @default.
- W3165855571 hasRelatedWork W3167935049 @default.
- W3165855571 hasRelatedWork W3193565141 @default.
- W3165855571 hasRelatedWork W4226493464 @default.
- W3165855571 hasRelatedWork W4300037846 @default.
- W3165855571 hasRelatedWork W4312417841 @default.
- W3165855571 hasRelatedWork W4376608589 @default.
- W3165855571 hasRelatedWork W4380075502 @default.
- W3165855571 isParatext "false" @default.
- W3165855571 isRetracted "false" @default.
- W3165855571 magId "3165855571" @default.
- W3165855571 workType "article" @default.