FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3150559585> ?p ?o ?g. }

• W3150559585 endingPage "106074" @default.
• W3150559585 startingPage "106074" @default.
• W3150559585 abstract "Background and objective: Lower back pain in humans has become a major risk. Classical approaches follow a non-invasive imaging technique for the assessment of spinal intervertebral disc (IVDs) abnormalities, where identification and segmentation of discs are done separately, making it a time-consuming phenomenon. This necessitates designing a robust automated and simultaneous IVDs identification and segmentation of multi-modality MRI images. Methods: We introduced a novel deep neural network architecture coined as ‘RIMNet’, a Region-to-Image Matching Network model, capable of performing an automated and simultaneous IVDs identification and segmentation of MRI images. The multi-modal input data is being fed to the network with a dropout strategy, by randomly disabling modalities in mini-batches. The performance accuracy as a function of the testing dataset was determined. The execution of the deep neural network model was evaluated by computing the IVDs Identification Accuracy, Dice coefficient, MDOC, Average Symmetric Surface Distance, Jaccard Coefficient, Hausdorff Distance and F1 Score. Results:Proposed model has attained 94% identification accuracy, dice coefficient value of 91.7±1% in segmentation and MDOC 90.2±1%. Our model also achieved 0.87±0.02 for Jaccard Coefficient, 0.54±0.04 for ASD and 0.62±0.02 mm Hausdorff Distance. The results have been validated and compared with other methodologies on dataset of MICCAI IVD 2018 challenge. Conclusions: Our proposed deep-learning methodology is capable of performing simultaneous identification and segmentation on IVDs MRI images of the human spine with high accuracy." @default.
• W3150559585 created "2021-04-13" @default.
• W3150559585 creator A5008303475 @default.
• W3150559585 creator A5033161553 @default.
• W3150559585 creator A5043543748 @default.
• W3150559585 creator A5044085104 @default.
• W3150559585 creator A5047098233 @default.
• W3150559585 date "2021-06-01" @default.
• W3150559585 modified "2023-10-17" @default.
• W3150559585 title "Deep neural network for automated simultaneous intervertebral disc (IVDs) identification and segmentation of multi-modal MR images" @default.
• W3150559585 cites W1901129140 @default.
• W3150559585 cites W2005971180 @default.
• W3150559585 cites W2023370307 @default.
• W3150559585 cites W2024440055 @default.
• W3150559585 cites W2031489346 @default.
• W3150559585 cites W2038085285 @default.
• W3150559585 cites W2060499860 @default.
• W3150559585 cites W2084111378 @default.
• W3150559585 cites W2084765810 @default.
• W3150559585 cites W2092416145 @default.
• W3150559585 cites W2093861573 @default.
• W3150559585 cites W2097583462 @default.
• W3150559585 cites W2111381594 @default.
• W3150559585 cites W2121578625 @default.
• W3150559585 cites W2155893237 @default.
• W3150559585 cites W2165759407 @default.
• W3150559585 cites W2167810128 @default.
• W3150559585 cites W2310992461 @default.
• W3150559585 cites W2395611524 @default.
• W3150559585 cites W2513411538 @default.
• W3150559585 cites W2782833026 @default.
• W3150559585 cites W2792023360 @default.
• W3150559585 cites W2793444752 @default.
• W3150559585 cites W2803575519 @default.
• W3150559585 cites W2810644003 @default.
• W3150559585 cites W2963931909 @default.
• W3150559585 cites W3006982732 @default.
• W3150559585 cites W3029869524 @default.
• W3150559585 doi "https://doi.org/10.1016/j.cmpb.2021.106074" @default.
• W3150559585 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/33906011" @default.
• W3150559585 hasPublicationYear "2021" @default.
• W3150559585 type Work @default.
• W3150559585 sameAs 3150559585 @default.
• W3150559585 citedByCount "11" @default.
• W3150559585 countsByYear W31505595852021 @default.
• W3150559585 countsByYear W31505595852022 @default.
• W3150559585 countsByYear W31505595852023 @default.
• W3150559585 crossrefType "journal-article" @default.
• W3150559585 hasAuthorship W3150559585A5008303475 @default.
• W3150559585 hasAuthorship W3150559585A5033161553 @default.
• W3150559585 hasAuthorship W3150559585A5043543748 @default.
• W3150559585 hasAuthorship W3150559585A5044085104 @default.
• W3150559585 hasAuthorship W3150559585A5047098233 @default.
• W3150559585 hasConcept C103278499 @default.
• W3150559585 hasConcept C108583219 @default.
• W3150559585 hasConcept C115961682 @default.
• W3150559585 hasConcept C116834253 @default.
• W3150559585 hasConcept C124504099 @default.
• W3150559585 hasConcept C141898687 @default.
• W3150559585 hasConcept C153180895 @default.
• W3150559585 hasConcept C154945302 @default.
• W3150559585 hasConcept C163892561 @default.
• W3150559585 hasConcept C203519979 @default.
• W3150559585 hasConcept C31972630 @default.
• W3150559585 hasConcept C41008148 @default.
• W3150559585 hasConcept C50644808 @default.
• W3150559585 hasConcept C59822182 @default.
• W3150559585 hasConcept C81363708 @default.
• W3150559585 hasConcept C86803240 @default.
• W3150559585 hasConcept C89600930 @default.
• W3150559585 hasConceptScore W3150559585C103278499 @default.
• W3150559585 hasConceptScore W3150559585C108583219 @default.
• W3150559585 hasConceptScore W3150559585C115961682 @default.
• W3150559585 hasConceptScore W3150559585C116834253 @default.
• W3150559585 hasConceptScore W3150559585C124504099 @default.
• W3150559585 hasConceptScore W3150559585C141898687 @default.
• W3150559585 hasConceptScore W3150559585C153180895 @default.
• W3150559585 hasConceptScore W3150559585C154945302 @default.
• W3150559585 hasConceptScore W3150559585C163892561 @default.
• W3150559585 hasConceptScore W3150559585C203519979 @default.
• W3150559585 hasConceptScore W3150559585C31972630 @default.
• W3150559585 hasConceptScore W3150559585C41008148 @default.
• W3150559585 hasConceptScore W3150559585C50644808 @default.
• W3150559585 hasConceptScore W3150559585C59822182 @default.
• W3150559585 hasConceptScore W3150559585C81363708 @default.
• W3150559585 hasConceptScore W3150559585C86803240 @default.
• W3150559585 hasConceptScore W3150559585C89600930 @default.
• W3150559585 hasFunder F4320325936 @default.
• W3150559585 hasLocation W31505595851 @default.
• W3150559585 hasOpenAccess W3150559585 @default.
• W3150559585 hasPrimaryLocation W31505595851 @default.
• W3150559585 hasRelatedWork W2593228870 @default.
• W3150559585 hasRelatedWork W2630229246 @default.
• W3150559585 hasRelatedWork W2769435486 @default.
• W3150559585 hasRelatedWork W2969790209 @default.
• W3150559585 hasRelatedWork W2998885888 @default.
• W3150559585 hasRelatedWork W3116883888 @default.
• W3150559585 hasRelatedWork W3135174555 @default.

• next