Confidence-based ensemble for GBM brain tumor segmentation ...
ui.adsabs.harvard.edu › abs › abstract
It is a challenging task to automatically segment glioblastoma multiforme (GBM) brain tumors on T1w post-contrast isotropic MR images.
It is a challenging task to automatically segment glioblastoma multiforme (GBM) brain tumors on T1w post-contrast isotropic MR images. A semi-automated system ...
The goal of this study was to develop an ensemble segmentation framework for glioblastoma multiforme tumors on single-channel T1w postcontrast magnetic ...
It is a challenging task to automatically segment glioblastoma multiforme (GBM) brain tumors on T1w post-contrast isotropic MR images.
It is a challenging task to automatically segment glioblastoma multiforme (GBM) brain tumors on T1w post-contrast isotropic MR images.
Aug 20, 2013 · Purpose: Ensemble segmentation methods combine the segmentation results of individual methods into a final one, with the goal of achieving ...
It is a challenging task to automatically segment glioblastoma multiforme (GBM) brain tumors on T1w post-contrast isotropic MR images.
A confidence map averaging (CMA) method was used as the ensemble rule. Results The performance is evaluated on a comprehensive dataset of 46 cases including ...
Ensemble segmentation for GBM brain tumors on MR images using confidence-based averaging. ... A brain tumor segmentation framework based on outlier detection*1.
People also ask
What is segmentation approach for brain tumor detection?
What is brain tumor segmentation 2024?
What is the most effective treatment for GBM?
Which algorithm is best for brain tumor detection?
A semi-automatic method that segments a brain tumor by training and generalizing within that brain only, based on some minimum user interaction is proposed, ...