FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3129063931> ?p ?o ?g. }

• W3129063931 endingPage "11653" @default.
• W3129063931 startingPage "11643" @default.
• W3129063931 abstract "In the clinical environment, myocardial infarction (MI) as one common cardiovascular disease is mainly evaluated using late gadolinium enhancement (LGE) cardiac magnetic resonance images (CMRIs). Accurate segmentation of the ventricles and the myocardium is a prerequisite for quantitative assessment of cardiac functions and disease progression. Performing the task using LGE images is, however, rather challenging due to heterogeneous image intensity distribution and lack of clear boundaries between adjacent organs and tissues. In this paper we propose a deep neural network method for automatic segmentation of the left ventricle (LV), right ventricle (RV), and left ventricular myocardium (LVM) from LGE CMRIs, which also leverages complementary information from cine and T2-weighted CMRIs if available. In the proposed method, termed SK-Unet, we augment the original U-Net model by adding a squeeze-and-excitation residual (SE-Res) module in the encoder and a selective kernel (SK) module in the decoder. The SE-Res module applies an attention mechanism to enhance informative feature extraction and suppress redundant ones. The SK module offers the ability to adaptively learn task-relevant multi-scale spatial features. We tested our method by participating in the MICCAI 2019 MS-CMRSeg challenge and achieved a mean dice score of 0.922 for LV segmentation, 0.827 for LVM, and 0.874 for RV. The results placed our method at the 1st place in the competition, and our accuracy of 0.827 also greatly surpasses the measured inter-observer agreement of 0.757 for manual segmentation of LVM in LGE CMRIs. The code accompanying our method is made available online at <uri>https://github.com/Xiyue-Wang/1st-in-MS-CMRSeg-2019</uri>." @default.
• W3129063931 created "2021-02-15" @default.
• W3129063931 creator A5031467394 @default.
• W3129063931 creator A5036620967 @default.
• W3129063931 creator A5036647389 @default.
• W3129063931 creator A5044137184 @default.
• W3129063931 creator A5057464765 @default.
• W3129063931 creator A5059639079 @default.
• W3129063931 creator A5061309609 @default.
• W3129063931 date "2021-05-15" @default.
• W3129063931 modified "2023-10-14" @default.
• W3129063931 title "SK-Unet: An Improved U-Net Model With Selective Kernel for the Segmentation of LGE Cardiac MR Images" @default.
• W3129063931 cites W1767244069 @default.
• W3129063931 cites W1981136868 @default.
• W3129063931 cites W1998223127 @default.
• W3129063931 cites W2025362214 @default.
• W3129063931 cites W2078877999 @default.
• W3129063931 cites W2106033751 @default.
• W3129063931 cites W2142384624 @default.
• W3129063931 cites W2147874932 @default.
• W3129063931 cites W2301358467 @default.
• W3129063931 cites W2441649867 @default.
• W3129063931 cites W2513411538 @default.
• W3129063931 cites W2580735716 @default.
• W3129063931 cites W2752782242 @default.
• W3129063931 cites W2823686338 @default.
• W3129063931 cites W2884436604 @default.
• W3129063931 cites W2901161734 @default.
• W3129063931 cites W2920149494 @default.
• W3129063931 cites W2921781974 @default.
• W3129063931 cites W2922509574 @default.
• W3129063931 cites W2951464021 @default.
• W3129063931 cites W2963881378 @default.
• W3129063931 cites W2964043069 @default.
• W3129063931 cites W2964212292 @default.
• W3129063931 cites W2979448322 @default.
• W3129063931 cites W2995848654 @default.
• W3129063931 cites W3000054715 @default.
• W3129063931 cites W3090384914 @default.
• W3129063931 doi "https://doi.org/10.1109/jsen.2021.3056131" @default.
• W3129063931 hasPublicationYear "2021" @default.
• W3129063931 type Work @default.
• W3129063931 sameAs 3129063931 @default.
• W3129063931 citedByCount "10" @default.
• W3129063931 countsByYear W31290639312020 @default.
• W3129063931 countsByYear W31290639312021 @default.
• W3129063931 countsByYear W31290639312022 @default.
• W3129063931 countsByYear W31290639312023 @default.
• W3129063931 crossrefType "journal-article" @default.
• W3129063931 hasAuthorship W3129063931A5031467394 @default.
• W3129063931 hasAuthorship W3129063931A5036620967 @default.
• W3129063931 hasAuthorship W3129063931A5036647389 @default.
• W3129063931 hasAuthorship W3129063931A5044137184 @default.
• W3129063931 hasAuthorship W3129063931A5057464765 @default.
• W3129063931 hasAuthorship W3129063931A5059639079 @default.
• W3129063931 hasAuthorship W3129063931A5061309609 @default.
• W3129063931 hasConcept C111919701 @default.
• W3129063931 hasConcept C118505674 @default.
• W3129063931 hasConcept C124504099 @default.
• W3129063931 hasConcept C126838900 @default.
• W3129063931 hasConcept C143409427 @default.
• W3129063931 hasConcept C153180895 @default.
• W3129063931 hasConcept C154945302 @default.
• W3129063931 hasConcept C164705383 @default.
• W3129063931 hasConcept C2778921608 @default.
• W3129063931 hasConcept C31972630 @default.
• W3129063931 hasConcept C41008148 @default.
• W3129063931 hasConcept C71924100 @default.
• W3129063931 hasConcept C89600930 @default.
• W3129063931 hasConceptScore W3129063931C111919701 @default.
• W3129063931 hasConceptScore W3129063931C118505674 @default.
• W3129063931 hasConceptScore W3129063931C124504099 @default.
• W3129063931 hasConceptScore W3129063931C126838900 @default.
• W3129063931 hasConceptScore W3129063931C143409427 @default.
• W3129063931 hasConceptScore W3129063931C153180895 @default.
• W3129063931 hasConceptScore W3129063931C154945302 @default.
• W3129063931 hasConceptScore W3129063931C164705383 @default.
• W3129063931 hasConceptScore W3129063931C2778921608 @default.
• W3129063931 hasConceptScore W3129063931C31972630 @default.
• W3129063931 hasConceptScore W3129063931C41008148 @default.
• W3129063931 hasConceptScore W3129063931C71924100 @default.
• W3129063931 hasConceptScore W3129063931C89600930 @default.
• W3129063931 hasFunder F4320321001 @default.
• W3129063931 hasFunder F4320334950 @default.
• W3129063931 hasIssue "10" @default.
• W3129063931 hasLocation W31290639311 @default.
• W3129063931 hasOpenAccess W3129063931 @default.
• W3129063931 hasPrimaryLocation W31290639311 @default.
• W3129063931 hasRelatedWork W1522196789 @default.
• W3129063931 hasRelatedWork W2022094567 @default.
• W3129063931 hasRelatedWork W2353214236 @default.
• W3129063931 hasRelatedWork W2393441460 @default.
• W3129063931 hasRelatedWork W2393721403 @default.
• W3129063931 hasRelatedWork W2402911890 @default.
• W3129063931 hasRelatedWork W2412248164 @default.
• W3129063931 hasRelatedWork W2418850124 @default.
• W3129063931 hasRelatedWork W3025229005 @default.
• W3129063931 hasRelatedWork W3187388830 @default.

• next