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Radiomics-based convolutional neural network for brain tumor segmentation on multiparametric magnetic resonance imaging
Accurate segmentation of gliomas on routine magnetic resonance image (MRI) scans plays an important role in disease diagnosis, prognosis, and patient treatment planning. We present a fully automated approach, radiomics-based convolutional neural network (RadCNN), for segmenting both high- and low-gr...
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| Pubblicato in: | J Med Imaging (Bellingham) |
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| Autori principali: | , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Society of Photo-Optical Instrumentation Engineers
2019
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6503346/ https://ncbi.nlm.nih.gov/pubmed/31093517 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1117/1.JMI.6.2.024005 |
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