Automated Segmentation of Hyperintense Regions in FLAIR MRI Using Deep Learning

We present a deep convolutional neural network application based on autoencoders aimed at segmentation of increased signal regions in fluid-attenuated inversion recovery magnetic resonance imaging images. The convolutional autoencoders were trained on the publicly available Brain Tumor Image Segment...

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Detalles Bibliográficos
Autores principales: Korfiatis, Panagiotis, Kline, Timothy L., Erickson, Bradley J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Grapho Publications, LLC 2016
Materias:
Research Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5215737/
https://www.ncbi.nlm.nih.gov/pubmed/28066806
http://dx.doi.org/10.18383/j.tom.2016.00166

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5215737/
https://www.ncbi.nlm.nih.gov/pubmed/28066806
http://dx.doi.org/10.18383/j.tom.2016.00166

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