Methods on skull stripping of MRI head scan images—a review
P Kalavathi, VBS Prasath - Journal of digital imaging, 2016 - Springer
The high resolution magnetic resonance (MR) brain images contain some non-brain tissues
such as skin, fat, muscle, neck, and eye balls compared to the functional images namely …
such as skin, fat, muscle, neck, and eye balls compared to the functional images namely …
Conventional and deep learning methods for skull stripping in brain MRI
HZU Rehman, H Hwang, S Lee - Applied Sciences, 2020 - mdpi.com
Featured Application Skull stripping is the most prevalent brain image analysis method. This
method can be applied to areas such as brain tissue segmentation and volumetric …
method can be applied to areas such as brain tissue segmentation and volumetric …
Optimizing parameter choice for FSL-Brain Extraction Tool (BET) on 3D T1 images in multiple sclerosis
V Popescu, M Battaglini, WS Hoogstrate, SCJ Verfaillie… - Neuroimage, 2012 - Elsevier
BACKGROUND: Brain atrophy studies often use FSL-BET (Brain Extraction Tool) as the first
step of image processing. Default BET does not always give satisfactory results on 3DT1 MR …
step of image processing. Default BET does not always give satisfactory results on 3DT1 MR …
A learning-based wrapper method to correct systematic errors in automatic image segmentation: consistently improved performance in hippocampus, cortex and brain …
We propose a simple but generally applicable approach to improving the accuracy of
automatic image segmentation algorithms relative to manual segmentations. The approach …
automatic image segmentation algorithms relative to manual segmentations. The approach …
A general skull stripping of multiparametric brain MRIs using 3D convolutional neural network
Accurate skull stripping facilitates following neuro-image analysis. For computer-aided
methods, the presence of brain skull in structural magnetic resonance imaging (MRI) …
methods, the presence of brain skull in structural magnetic resonance imaging (MRI) …
Infant brain extraction in T1-weighted MR images using BET and refinement using LCDG and MGRF models
In this paper, we propose a novel framework for the automated extraction of the brain from
T1-weighted MR images. The proposed approach is primarily based on the integration of a …
T1-weighted MR images. The proposed approach is primarily based on the integration of a …
State-of-the-art traditional to the machine-and deep-learning-based skull stripping techniques, models, and algorithms
Several neuroimaging processing applications consider skull stripping as a crucial pre-
processing step. Due to complex anatomical brain structure and intensity variations in brain …
processing step. Due to complex anatomical brain structure and intensity variations in brain …
An accurate skull stripping method based on simplex meshes and histogram analysis for magnetic resonance images
FJ Galdames, F Jaillet, CA Perez - Journal of neuroscience methods, 2012 - Elsevier
Skull stripping methods are designed to eliminate the non-brain tissue in magnetic
resonance (MR) brain images. Removal of non-brain tissues is a fundamental step in …
resonance (MR) brain images. Removal of non-brain tissues is a fundamental step in …
Differences in white matter abnormalities between bipolar I and II disorders
JX Liu, YS Chen, JC Hsieh, TP Su, TC Yeh… - Journal of affective …, 2010 - Elsevier
BACKGROUND: Although patients with bipolar I and II disorders exhibit heterogeneous
clinical presentations and cognitive functions, it remains unclear whether these two subtypes …
clinical presentations and cognitive functions, it remains unclear whether these two subtypes …
Segmentation of infant brain using nonnegative matrix factorization
This study develops an atlas-based automated framework for segmenting infants' brains
from magnetic resonance imaging (MRI). For the accurate segmentation of different …
from magnetic resonance imaging (MRI). For the accurate segmentation of different …