Supervised Brain Tumor Segmentation Based on Gradient and Context-Sensitive Features

Supervised Brain Tumor Segmentation Based on Gradient and Context-Sensitive Features

Gliomas have the highest mortality rate and prevalence among the primary brain tumors. In this study, we proposed a supervised brain tumor segmentation method which detects diverse tumoral structures of both high grade gliomas and low grade gliomas in magnetic resonance imaging (MRI) images based on...

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Bibliographic Details
Main Authors: Junting Zhao, Zhaopeng Meng, Leyi Wei, Changming Sun, Quan Zou, Ran Su
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-03-01
Series:Frontiers in Neuroscience
Subjects:
brain tumor segmentation
gradient
context-sensitive
random forest
mRMR
class-imbalanced
Online Access:https://www.frontiersin.org/article/10.3389/fnins.2019.00144/full

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