Deep convolutional neural networks for automated segmentation of brain metastases trained on clinical data

Abstract Introduction Deep learning-based algorithms have demonstrated enormous performance in segmentation of medical images. We collected a dataset of multiparametric MRI and contour data acquired for use in radiosurgery, to evaluate the performance of deep convolutional neural networks (DCNN) in...

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Detalhes bibliográficos
Principais autores: Khaled Bousabarah, Maximilian Ruge, Julia-Sarita Brand, Mauritius Hoevels, Daniel Rueß, Jan Borggrefe, Nils Große Hokamp, Veerle Visser-Vandewalle, David Maintz, Harald Treuer, Martin Kocher
Formato: Artigo
Idioma:Inglês
Publicado em: BMC 2020-04-01
coleção:Radiation Oncology
Assuntos:
Brain metastasis
Magnetic resonance imaging
Deep learning
Segmentation
Stereotactic radiosurgery
Acesso em linha:http://link.springer.com/article/10.1186/s13014-020-01514-6
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