FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3085882733> ?p ?o ?g. }

• W3085882733 endingPage "1611" @default.
• W3085882733 startingPage "1601" @default.
• W3085882733 abstract "Pancreas identification and segmentation is an essential task in the diagnosis and prognosis of pancreas disease. Although deep neural networks have been widely applied in abdominal organ segmentation, it is still challenging for small organs (e.g. pancreas) that present low contrast, highly flexible anatomical structure and relatively small region. In recent years, coarse-to-fine methods have improved pancreas segmentation accuracy by using coarse predictions in the fine stage, but only object location is utilized and rich image context is neglected. In this paper, we propose a novel distance-based saliency-aware model, namely DSD-ASPP-Net, to fully use coarse segmentation to highlight the pancreas feature and boost accuracy in the fine segmentation stage. Specifically, a DenseASPP (Dense Atrous Spatial Pyramid Pooling) model is trained to learn the pancreas location and probability map, which is then transformed into saliency map through geodesic distance-based saliency transformation. In the fine stage, saliency-aware modules that combine saliency map and image context are introduced into DenseASPP to develop the DSD-ASPP-Net. The architecture of DenseASPP brings multi-scale feature representation and achieves larger receptive field in a denser way, which overcome the difficulties brought by variable object sizes and locations. Our method was evaluated on both public NIH pancreas dataset and local hospital dataset, and achieved an average Dice-Sørensen Coefficient (DSC) value of 85.49±4.77% on the NIH dataset, outperforming former coarse-to-fine methods." @default.
• W3085882733 created "2020-09-21" @default.
• W3085882733 creator A5004969274 @default.
• W3085882733 creator A5018090414 @default.
• W3085882733 creator A5019755934 @default.
• W3085882733 creator A5023138112 @default.
• W3085882733 creator A5039356472 @default.
• W3085882733 creator A5044014447 @default.
• W3085882733 creator A5056900515 @default.
• W3085882733 creator A5057311321 @default.
• W3085882733 creator A5081971554 @default.
• W3085882733 date "2021-05-01" @default.
• W3085882733 modified "2023-10-15" @default.
• W3085882733 title "Automatic Pancreas Segmentation in CT Images With Distance-Based Saliency-Aware DenseASPP Network" @default.
• W3085882733 cites W1680164276 @default.
• W3085882733 cites W186896354 @default.
• W3085882733 cites W1884191083 @default.
• W3085882733 cites W1903029394 @default.
• W3085882733 cites W2000585255 @default.
• W3085882733 cites W2013488403 @default.
• W3085882733 cites W2108598243 @default.
• W3085882733 cites W2155343350 @default.
• W3085882733 cites W2260867322 @default.
• W3085882733 cites W2357815549 @default.
• W3085882733 cites W2412782625 @default.
• W3085882733 cites W2550380503 @default.
• W3085882733 cites W2555096873 @default.
• W3085882733 cites W2585890928 @default.
• W3085882733 cites W2618237340 @default.
• W3085882733 cites W2732931556 @default.
• W3085882733 cites W2751436279 @default.
• W3085882733 cites W2771252144 @default.
• W3085882733 cites W2792124446 @default.
• W3085882733 cites W2797038701 @default.
• W3085882733 cites W2799142782 @default.
• W3085882733 cites W2799213142 @default.
• W3085882733 cites W2886667086 @default.
• W3085882733 cites W2895056585 @default.
• W3085882733 cites W2909481502 @default.
• W3085882733 cites W2963446712 @default.
• W3085882733 cites W2964227007 @default.
• W3085882733 cites W2973867667 @default.
• W3085882733 cites W2979458288 @default.
• W3085882733 cites W2994879149 @default.
• W3085882733 cites W2996408713 @default.
• W3085882733 cites W2998316788 @default.
• W3085882733 cites W3002313441 @default.
• W3085882733 cites W3002943723 @default.
• W3085882733 cites W3104390926 @default.
• W3085882733 cites W377632744 @default.
• W3085882733 cites W855272188 @default.
• W3085882733 doi "https://doi.org/10.1109/jbhi.2020.3023462" @default.
• W3085882733 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/32915752" @default.
• W3085882733 hasPublicationYear "2021" @default.
• W3085882733 type Work @default.
• W3085882733 sameAs 3085882733 @default.
• W3085882733 citedByCount "17" @default.
• W3085882733 countsByYear W30858827332021 @default.
• W3085882733 countsByYear W30858827332022 @default.
• W3085882733 countsByYear W30858827332023 @default.
• W3085882733 crossrefType "journal-article" @default.
• W3085882733 hasAuthorship W3085882733A5004969274 @default.
• W3085882733 hasAuthorship W3085882733A5018090414 @default.
• W3085882733 hasAuthorship W3085882733A5019755934 @default.
• W3085882733 hasAuthorship W3085882733A5023138112 @default.
• W3085882733 hasAuthorship W3085882733A5039356472 @default.
• W3085882733 hasAuthorship W3085882733A5044014447 @default.
• W3085882733 hasAuthorship W3085882733A5056900515 @default.
• W3085882733 hasAuthorship W3085882733A5057311321 @default.
• W3085882733 hasAuthorship W3085882733A5081971554 @default.
• W3085882733 hasConcept C124504099 @default.
• W3085882733 hasConcept C134018914 @default.
• W3085882733 hasConcept C138885662 @default.
• W3085882733 hasConcept C142575187 @default.
• W3085882733 hasConcept C153180895 @default.
• W3085882733 hasConcept C154945302 @default.
• W3085882733 hasConcept C166957645 @default.
• W3085882733 hasConcept C205649164 @default.
• W3085882733 hasConcept C2524010 @default.
• W3085882733 hasConcept C2776401178 @default.
• W3085882733 hasConcept C2778764654 @default.
• W3085882733 hasConcept C2779343474 @default.
• W3085882733 hasConcept C31972630 @default.
• W3085882733 hasConcept C33923547 @default.
• W3085882733 hasConcept C41008148 @default.
• W3085882733 hasConcept C41895202 @default.
• W3085882733 hasConcept C70437156 @default.
• W3085882733 hasConcept C71924100 @default.
• W3085882733 hasConcept C89600930 @default.
• W3085882733 hasConceptScore W3085882733C124504099 @default.
• W3085882733 hasConceptScore W3085882733C134018914 @default.
• W3085882733 hasConceptScore W3085882733C138885662 @default.
• W3085882733 hasConceptScore W3085882733C142575187 @default.
• W3085882733 hasConceptScore W3085882733C153180895 @default.
• W3085882733 hasConceptScore W3085882733C154945302 @default.
• W3085882733 hasConceptScore W3085882733C166957645 @default.
• W3085882733 hasConceptScore W3085882733C205649164 @default.
• W3085882733 hasConceptScore W3085882733C2524010 @default.

• next