Fully automated segmentation of brain tumor from multiparametric MRI using 3D context u-net with deep supervision

Published: Feb 15, 2021
Abstract
Gliomas are very heterogenous set of tumors that grow within the substance of brain and often mix with normal brain tissues. Due to its histologic complexity and irregular shapes, multiparametric magnetic resonance imaging is used to accurately diagnose brain tumor and their subregions. Current practice requires physicians to manually segment these regions on a large image dataset, which can be a very time consuming and complicated task...
Paper Details
Title
Fully automated segmentation of brain tumor from multiparametric MRI using 3D context u-net with deep supervision
Published Date
Feb 15, 2021
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.