Matches in SemOpenAlex for { <https://semopenalex.org/work/W4213276948> ?p ?o ?g. }
Showing items 1 to 96 of
96
with 100 items per page.
- W4213276948 abstract "Latest advancements in deep learning have led to an enthusiasm among biomedical researchers to explore the field of semantic segmentation further. Lungs segmentation plays a crucial role in the computer-aided diagnosis of several lung diseases. However, various anatomical varieties make lungs segmentation a challenging task. The main objective of our study is to propose a modified U-Net model that automatically segments the lungs from the computed tomography images. The proposed algorithm is trained on 240 training images. The advantage of this architecture is that it consumes less data and GPU memory. Experimental results show that the proposed architecture obtained 98.3% accuracy, 96.29% dice coefficient, and 93.63% Jaccard index. The segmentation model outperformed the original U-Net and the state-of-the-art methods. Thus, the modified U-Net model is apt for accurate lung segmentation." @default.
- W4213276948 created "2022-02-24" @default.
- W4213276948 creator A5019300933 @default.
- W4213276948 creator A5023953048 @default.
- W4213276948 creator A5058656783 @default.
- W4213276948 creator A5089709459 @default.
- W4213276948 date "2021-12-15" @default.
- W4213276948 modified "2023-10-05" @default.
- W4213276948 title "Semantic segmentation of lungs using a modified U-Net architecture through limited Computed Tomography images" @default.
- W4213276948 cites W1986649315 @default.
- W4213276948 cites W2247287081 @default.
- W4213276948 cites W2520732917 @default.
- W4213276948 cites W2793954249 @default.
- W4213276948 cites W2901188035 @default.
- W4213276948 cites W2902972155 @default.
- W4213276948 cites W2941458854 @default.
- W4213276948 cites W2963881378 @default.
- W4213276948 cites W2990389191 @default.
- W4213276948 cites W2991286928 @default.
- W4213276948 cites W3016237374 @default.
- W4213276948 cites W3016312932 @default.
- W4213276948 cites W3049459429 @default.
- W4213276948 cites W3104561312 @default.
- W4213276948 cites W3120253959 @default.
- W4213276948 cites W3129739079 @default.
- W4213276948 cites W3135174555 @default.
- W4213276948 cites W3137734413 @default.
- W4213276948 cites W3158290426 @default.
- W4213276948 cites W3159751348 @default.
- W4213276948 cites W3171869748 @default.
- W4213276948 cites W3176469180 @default.
- W4213276948 doi "https://doi.org/10.1109/acts53447.2021.9708190" @default.
- W4213276948 hasPublicationYear "2021" @default.
- W4213276948 type Work @default.
- W4213276948 citedByCount "4" @default.
- W4213276948 countsByYear W42132769482023 @default.
- W4213276948 crossrefType "proceedings-article" @default.
- W4213276948 hasAuthorship W4213276948A5019300933 @default.
- W4213276948 hasAuthorship W4213276948A5023953048 @default.
- W4213276948 hasAuthorship W4213276948A5058656783 @default.
- W4213276948 hasAuthorship W4213276948A5089709459 @default.
- W4213276948 hasConcept C108583219 @default.
- W4213276948 hasConcept C123657996 @default.
- W4213276948 hasConcept C124504099 @default.
- W4213276948 hasConcept C126838900 @default.
- W4213276948 hasConcept C142362112 @default.
- W4213276948 hasConcept C153180895 @default.
- W4213276948 hasConcept C153349607 @default.
- W4213276948 hasConcept C154945302 @default.
- W4213276948 hasConcept C163892561 @default.
- W4213276948 hasConcept C203519979 @default.
- W4213276948 hasConcept C22029948 @default.
- W4213276948 hasConcept C2524010 @default.
- W4213276948 hasConcept C31972630 @default.
- W4213276948 hasConcept C33923547 @default.
- W4213276948 hasConcept C41008148 @default.
- W4213276948 hasConcept C544519230 @default.
- W4213276948 hasConcept C65885262 @default.
- W4213276948 hasConcept C71924100 @default.
- W4213276948 hasConcept C89600930 @default.
- W4213276948 hasConceptScore W4213276948C108583219 @default.
- W4213276948 hasConceptScore W4213276948C123657996 @default.
- W4213276948 hasConceptScore W4213276948C124504099 @default.
- W4213276948 hasConceptScore W4213276948C126838900 @default.
- W4213276948 hasConceptScore W4213276948C142362112 @default.
- W4213276948 hasConceptScore W4213276948C153180895 @default.
- W4213276948 hasConceptScore W4213276948C153349607 @default.
- W4213276948 hasConceptScore W4213276948C154945302 @default.
- W4213276948 hasConceptScore W4213276948C163892561 @default.
- W4213276948 hasConceptScore W4213276948C203519979 @default.
- W4213276948 hasConceptScore W4213276948C22029948 @default.
- W4213276948 hasConceptScore W4213276948C2524010 @default.
- W4213276948 hasConceptScore W4213276948C31972630 @default.
- W4213276948 hasConceptScore W4213276948C33923547 @default.
- W4213276948 hasConceptScore W4213276948C41008148 @default.
- W4213276948 hasConceptScore W4213276948C544519230 @default.
- W4213276948 hasConceptScore W4213276948C65885262 @default.
- W4213276948 hasConceptScore W4213276948C71924100 @default.
- W4213276948 hasConceptScore W4213276948C89600930 @default.
- W4213276948 hasFunder F4320334771 @default.
- W4213276948 hasLocation W42132769481 @default.
- W4213276948 hasOpenAccess W4213276948 @default.
- W4213276948 hasPrimaryLocation W42132769481 @default.
- W4213276948 hasRelatedWork W2914580601 @default.
- W4213276948 hasRelatedWork W2999580839 @default.
- W4213276948 hasRelatedWork W3093926553 @default.
- W4213276948 hasRelatedWork W3094077541 @default.
- W4213276948 hasRelatedWork W3116883888 @default.
- W4213276948 hasRelatedWork W3120092106 @default.
- W4213276948 hasRelatedWork W4287631720 @default.
- W4213276948 hasRelatedWork W4295442860 @default.
- W4213276948 hasRelatedWork W4310202196 @default.
- W4213276948 hasRelatedWork W4315491877 @default.
- W4213276948 isParatext "false" @default.
- W4213276948 isRetracted "false" @default.
- W4213276948 workType "article" @default.