FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3198571567> ?p ?o ?g. }

• W3198571567 endingPage "1707" @default.
• W3198571567 startingPage "1696" @default.
• W3198571567 abstract "Laryngeal cancer tumor (LCT) grading is a challenging task in P63 Immunohistochemical (IHC) histopathology images due to small differences between LCT levels in pathology images, the lack of precision in lesion regions of interest (LROIs) and the paucity of LCT pathology image samples. The key to solving the LCT grading problem is to transfer knowledge from other images and to identify more accurate LROIs, but the following problems occur: 1) transferring knowledge without a priori experience often causes negative transfer and creates a heavy workload due to the abundance of image types, and 2) convolutional neural networks (CNNs) constructing deep models by stacking cannot sufficiently identify LROIs, often deviate significantly from the LROIs focused on by experienced pathologists, and are prone to providing misleading second opinions. So we propose a novel fusion attention block network (FABNet) to address these problems. First, we propose a model transfer method based on clinical a priori experience and sample analysis (CPESA) that analyzes the transfer ability by integrating clinical a priori experience using indicators such as the relationship between the cancer onset location and morphology and the texture and staining degree of cell nuclei in histopathology images; our method further validates these indicators by the probability distribution of cancer image samples. Then, we propose a fusion attention block (FAB) structure, which can both provide an advanced non-uniform sparse representation of images and extract spatial relationship information between nuclei; consequently, the LROI can be more accurate and more relevant to pathologists. We conducted extensive experiments, compared with the best Baseline model, the classification accuracy is improved 25%, and It is demonstrated that FABNet performs better on different cancer pathology image datasets and outperforms other state of the art (SOTA) models." @default.
• W3198571567 created "2021-09-13" @default.
• W3198571567 creator A5004599844 @default.
• W3198571567 creator A5023695406 @default.
• W3198571567 creator A5037654021 @default.
• W3198571567 creator A5044075152 @default.
• W3198571567 creator A5054333186 @default.
• W3198571567 creator A5063528801 @default.
• W3198571567 date "2022-04-01" @default.
• W3198571567 modified "2023-10-03" @default.
• W3198571567 title "FABNet: Fusion Attention Block and Transfer Learning for Laryngeal Cancer Tumor Grading in P63 IHC Histopathology Images" @default.
• W3198571567 cites W1611161535 @default.
• W3198571567 cites W1986213213 @default.
• W3198571567 cites W1987026408 @default.
• W3198571567 cites W2097117768 @default.
• W3198571567 cites W2103243046 @default.
• W3198571567 cites W2113022856 @default.
• W3198571567 cites W2151608510 @default.
• W3198571567 cites W2183341477 @default.
• W3198571567 cites W2194775991 @default.
• W3198571567 cites W2248620004 @default.
• W3198571567 cites W2395579298 @default.
• W3198571567 cites W2531409750 @default.
• W3198571567 cites W2772723798 @default.
• W3198571567 cites W2890554424 @default.
• W3198571567 cites W2899380210 @default.
• W3198571567 cites W2912387879 @default.
• W3198571567 cites W2922005212 @default.
• W3198571567 cites W2940469730 @default.
• W3198571567 cites W2958255666 @default.
• W3198571567 cites W2962858109 @default.
• W3198571567 cites W2963091558 @default.
• W3198571567 cites W2963420686 @default.
• W3198571567 cites W2963446712 @default.
• W3198571567 cites W2981137547 @default.
• W3198571567 cites W2982651654 @default.
• W3198571567 cites W3003581523 @default.
• W3198571567 cites W3021186055 @default.
• W3198571567 cites W3043535018 @default.
• W3198571567 cites W3084299163 @default.
• W3198571567 cites W3084893494 @default.
• W3198571567 cites W3088629580 @default.
• W3198571567 cites W3100084586 @default.
• W3198571567 cites W3100398151 @default.
• W3198571567 cites W3104138698 @default.
• W3198571567 cites W3121859091 @default.
• W3198571567 doi "https://doi.org/10.1109/jbhi.2021.3108999" @default.
• W3198571567 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/34469320" @default.
• W3198571567 hasPublicationYear "2022" @default.
• W3198571567 type Work @default.
• W3198571567 sameAs 3198571567 @default.
• W3198571567 citedByCount "12" @default.
• W3198571567 countsByYear W31985715672022 @default.
• W3198571567 countsByYear W31985715672023 @default.
• W3198571567 crossrefType "journal-article" @default.
• W3198571567 hasAuthorship W3198571567A5004599844 @default.
• W3198571567 hasAuthorship W3198571567A5023695406 @default.
• W3198571567 hasAuthorship W3198571567A5037654021 @default.
• W3198571567 hasAuthorship W3198571567A5044075152 @default.
• W3198571567 hasAuthorship W3198571567A5054333186 @default.
• W3198571567 hasAuthorship W3198571567A5063528801 @default.
• W3198571567 hasConcept C111472728 @default.
• W3198571567 hasConcept C127413603 @default.
• W3198571567 hasConcept C138885662 @default.
• W3198571567 hasConcept C142724271 @default.
• W3198571567 hasConcept C147176958 @default.
• W3198571567 hasConcept C153180895 @default.
• W3198571567 hasConcept C154945302 @default.
• W3198571567 hasConcept C2777286243 @default.
• W3198571567 hasConcept C41008148 @default.
• W3198571567 hasConcept C544855455 @default.
• W3198571567 hasConcept C71924100 @default.
• W3198571567 hasConcept C75553542 @default.
• W3198571567 hasConcept C81363708 @default.
• W3198571567 hasConceptScore W3198571567C111472728 @default.
• W3198571567 hasConceptScore W3198571567C127413603 @default.
• W3198571567 hasConceptScore W3198571567C138885662 @default.
• W3198571567 hasConceptScore W3198571567C142724271 @default.
• W3198571567 hasConceptScore W3198571567C147176958 @default.
• W3198571567 hasConceptScore W3198571567C153180895 @default.
• W3198571567 hasConceptScore W3198571567C154945302 @default.
• W3198571567 hasConceptScore W3198571567C2777286243 @default.
• W3198571567 hasConceptScore W3198571567C41008148 @default.
• W3198571567 hasConceptScore W3198571567C544855455 @default.
• W3198571567 hasConceptScore W3198571567C71924100 @default.
• W3198571567 hasConceptScore W3198571567C75553542 @default.
• W3198571567 hasConceptScore W3198571567C81363708 @default.
• W3198571567 hasIssue "4" @default.
• W3198571567 hasLocation W31985715671 @default.
• W3198571567 hasLocation W31985715672 @default.
• W3198571567 hasOpenAccess W3198571567 @default.
• W3198571567 hasPrimaryLocation W31985715671 @default.
• W3198571567 hasRelatedWork W2175746458 @default.
• W3198571567 hasRelatedWork W2732542196 @default.
• W3198571567 hasRelatedWork W2738221750 @default.
• W3198571567 hasRelatedWork W2760085659 @default.
• W3198571567 hasRelatedWork W2883200793 @default.
• W3198571567 hasRelatedWork W2912288872 @default.

• next