| Registro completo |
| Provedor de dados: |
BJMBR
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| País: |
Brazil
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| Título: |
Manual and semiautomatic segmentation of bone sarcomas on MRI have high similarity
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| Autores: |
Dionísio,F.C.F.
Oliveira,L.S.
Hernandes,M.A.
Engel,E.E.
Rangayyan,R.M.
Azevedo-Marques,P.M.
Nogueira-Barbosa,M.H.
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| Data: |
2020-01-01
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| Ano: |
2020
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| Palavras-chave: |
Ewing sarcoma
Osteosarcoma
Manual segmentation
Semiautomatic segmentation
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| Resumo: |
The aims of this study were to evaluate the intra- and interobserver reproducibility of manual segmentation of bone sarcomas in magnetic resonance imaging (MRI) studies and to compare manual and semiautomatic segmentation methods. This retrospective study included twelve osteosarcoma and eight Ewing sarcoma MRI studies performed prior to any therapeutic intervention. All cases were histopathologically confirmed. Three radiologists used 3D-Slicer software to perform manual segmentation of bone sarcomas in a blinded and independent manner. One radiologist segmented manually and also performed semiautomatic segmentation with the GrowCut tool. Segmentation exercises were timed for comparison. The dice similarity coefficient (DSC) and Hausdorff distance (HD) were used to evaluate similarity between the segmentation results and further statistical analyses were performed to compare DSC, HD, and volumetric results. Manual segmentation was reproducible with intraobserver DSC varying from 0.83 to 0.97 and HD from 3.37 to 28.73 mm. Interobserver DSC of manual segmentation showed variation from 0.73 to 0.97 and HD from 3.93 to 33.40 mm. Semiautomatic segmentation compared to manual segmentation resulted in DSCs of 0.71−0.96 and HDs of 5.38−31.54 mm. Semiautomatic segmentation required significantly less time compared to manual segmentation (P value ≤0.05). Among all situations compared, tumor volumetry did not show significant statistical differences (P value >0.05). We found excellent intra- and interobserver agreement for manual segmentation of osteosarcoma and Ewing sarcoma. There was high similarity between manual and semiautomatic segmentation, with a significant reduction of segmentation time using the semiautomatic method.
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| Tipo: |
Info:eu-repo/semantics/article
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| Idioma: |
Inglês
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| Identificador: |
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-879X2020000200605
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| Editor: |
Associação Brasileira de Divulgação Científica
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| Relação: |
10.1590/1414-431x20198962
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| Formato: |
text/html
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| Fonte: |
Brazilian Journal of Medical and Biological Research v.53 n.2 2020
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| Direitos: |
info:eu-repo/semantics/openAccess
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