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Clinical Evaluation of a Multiparametric Deep Learning Model for Glioblastoma Segmentation Using Heterogeneous Magnetic Resonance Imaging Data From Clinical Routine
OBJECTIVES: The aims of this study were, first, to evaluate a deep learning–based, automatic glioblastoma (GB) tumor segmentation algorithm on clinical routine data from multiple centers and compare the results to a ground truth, manual expert segmentation, and second, to evaluate the quality of the...
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| Publicado no: | Invest Radiol |
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| Main Authors: | , , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Lippincott Williams & Wilkins
2018
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7598095/ https://ncbi.nlm.nih.gov/pubmed/29863600 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1097/RLI.0000000000000484 |
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