FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3044138845> ?p ?o ?g. }

• W3044138845 endingPage "1138" @default.
• W3044138845 startingPage "1128" @default.
• W3044138845 abstract "Blood vessel segmentation in fundus images is a critical procedure in the diagnosis of ophthalmic diseases. Recent deep learning methods achieve high accuracy in vessel segmentation but still face the challenge to segment the microvascular and detect the vessel boundary. This is due to the fact that common Convolutional Neural Networks (CNN) are unable to preserve rich spatial information and a large receptive field simultaneously. Besides, CNN models for vessel segmentation usually are trained by equal pixel level cross-entropy loss, which tend to miss fine vessel structures. In this paper, we propose a novel Context Spatial U-Net (CSU-Net) for blood vessel segmentation. Compared with the other U-Net based models, we design a two-channel encoder: a context channel with multi-scale convolution to capture more receptive field and a spatial channel with large kernel to retain spatial information. Also, to combine and strengthen the features extracted from two paths, we introduce a feature fusion module (FFM) and an attention skip module (ASM). Furthermore, we propose a structure loss, which adds a spatial weight to cross-entropy loss and guide the network to focus more on the thin vessels and boundaries. We evaluated this model on three public datasets: DRIVE, CHASE-DB1 and STARE. The results show that the CSU-Net achieves higher segmentation accuracy than the current state-of-the-art methods." @default.
• W3044138845 created "2020-07-29" @default.
• W3044138845 creator A5003799076 @default.
• W3044138845 creator A5031159788 @default.
• W3044138845 creator A5069531609 @default.
• W3044138845 creator A5077914684 @default.
• W3044138845 creator A5081041205 @default.
• W3044138845 creator A5084940574 @default.
• W3044138845 date "2021-04-01" @default.
• W3044138845 modified "2023-10-01" @default.
• W3044138845 title "CSU-Net: A Context Spatial U-Net for Accurate Blood Vessel Segmentation in Fundus Images" @default.
• W3044138845 cites W1903029394 @default.
• W3044138845 cites W2044880603 @default.
• W3044138845 cites W2045227075 @default.
• W3044138845 cites W2051578148 @default.
• W3044138845 cites W2053154970 @default.
• W3044138845 cites W2058333183 @default.
• W3044138845 cites W2072130234 @default.
• W3044138845 cites W2109037308 @default.
• W3044138845 cites W2112783556 @default.
• W3044138845 cites W2115680416 @default.
• W3044138845 cites W2123434300 @default.
• W3044138845 cites W2130054905 @default.
• W3044138845 cites W2132519114 @default.
• W3044138845 cites W2145305441 @default.
• W3044138845 cites W2150769593 @default.
• W3044138845 cites W2163344010 @default.
• W3044138845 cites W2166524747 @default.
• W3044138845 cites W2171459511 @default.
• W3044138845 cites W2206167351 @default.
• W3044138845 cites W2320230300 @default.
• W3044138845 cites W2327793514 @default.
• W3044138845 cites W2394979716 @default.
• W3044138845 cites W2412782625 @default.
• W3044138845 cites W2433259561 @default.
• W3044138845 cites W2436226714 @default.
• W3044138845 cites W2556022279 @default.
• W3044138845 cites W2560023338 @default.
• W3044138845 cites W2598666589 @default.
• W3044138845 cites W2606663706 @default.
• W3044138845 cites W2792951596 @default.
• W3044138845 cites W2802388893 @default.
• W3044138845 cites W2890192683 @default.
• W3044138845 cites W2898910301 @default.
• W3044138845 cites W2900328506 @default.
• W3044138845 cites W2907750714 @default.
• W3044138845 cites W2923997689 @default.
• W3044138845 doi "https://doi.org/10.1109/jbhi.2020.3011178" @default.
• W3044138845 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/32750968" @default.
• W3044138845 hasPublicationYear "2021" @default.
• W3044138845 type Work @default.
• W3044138845 sameAs 3044138845 @default.
• W3044138845 citedByCount "46" @default.
• W3044138845 countsByYear W30441388452021 @default.
• W3044138845 countsByYear W30441388452022 @default.
• W3044138845 countsByYear W30441388452023 @default.
• W3044138845 crossrefType "journal-article" @default.
• W3044138845 hasAuthorship W3044138845A5003799076 @default.
• W3044138845 hasAuthorship W3044138845A5031159788 @default.
• W3044138845 hasAuthorship W3044138845A5069531609 @default.
• W3044138845 hasAuthorship W3044138845A5077914684 @default.
• W3044138845 hasAuthorship W3044138845A5081041205 @default.
• W3044138845 hasAuthorship W3044138845A5084940574 @default.
• W3044138845 hasConcept C108583219 @default.
• W3044138845 hasConcept C118487528 @default.
• W3044138845 hasConcept C124504099 @default.
• W3044138845 hasConcept C138885662 @default.
• W3044138845 hasConcept C151730666 @default.
• W3044138845 hasConcept C153180895 @default.
• W3044138845 hasConcept C154945302 @default.
• W3044138845 hasConcept C167981619 @default.
• W3044138845 hasConcept C2776391266 @default.
• W3044138845 hasConcept C2776401178 @default.
• W3044138845 hasConcept C2779343474 @default.
• W3044138845 hasConcept C31972630 @default.
• W3044138845 hasConcept C41008148 @default.
• W3044138845 hasConcept C41895202 @default.
• W3044138845 hasConcept C64754055 @default.
• W3044138845 hasConcept C71924100 @default.
• W3044138845 hasConcept C81363708 @default.
• W3044138845 hasConcept C86803240 @default.
• W3044138845 hasConcept C89600930 @default.
• W3044138845 hasConceptScore W3044138845C108583219 @default.
• W3044138845 hasConceptScore W3044138845C118487528 @default.
• W3044138845 hasConceptScore W3044138845C124504099 @default.
• W3044138845 hasConceptScore W3044138845C138885662 @default.
• W3044138845 hasConceptScore W3044138845C151730666 @default.
• W3044138845 hasConceptScore W3044138845C153180895 @default.
• W3044138845 hasConceptScore W3044138845C154945302 @default.
• W3044138845 hasConceptScore W3044138845C167981619 @default.
• W3044138845 hasConceptScore W3044138845C2776391266 @default.
• W3044138845 hasConceptScore W3044138845C2776401178 @default.
• W3044138845 hasConceptScore W3044138845C2779343474 @default.
• W3044138845 hasConceptScore W3044138845C31972630 @default.
• W3044138845 hasConceptScore W3044138845C41008148 @default.
• W3044138845 hasConceptScore W3044138845C41895202 @default.
• W3044138845 hasConceptScore W3044138845C64754055 @default.
• W3044138845 hasConceptScore W3044138845C71924100 @default.

• next