Isolation of the brain from other tissue types in magnetic resonance (MR) images is an important step in many types of neuro-imaging research using both humans and animal subjects. The importance of brain extraction is well appreciated-numerous approaches have been published and the benefits of good extraction methods to subsequent processing are well known. We describe a tool-the marker based watershed scalper (MBWSS)-for isolating the brain in T1-weighted MR images built using filtering and segmentation components from the Insight Toolkit (ITK) framework. The key elements of MBWSS-the watershed transform from markers and aggressive filtering with large kernels-are techniques that have rarely been used in neuroimaging segmentation applicat...
Accurate and fully automatic segmentation of brain from magnetic resonance (MR)scans is a challengin...
We present an automated method for segmenting skull, scalp, and brain regions in T1-weighted MR imag...
Accurate brain tissue extraction on magnetic resonance imaging (MRI) data is crucial for analyzing b...
Isolation of the brain from other tissue types in magnetic resonance (MR) images is an important ste...
doi: 10.3389/fninf.2013.00032 Brain extraction using the watershed transform from marker
Extraction of the brain—i.e. cerebrum, cerebellum, and brain stem—from T1-weighted structural magnet...
An automated method for segmenting magnetic resonance head images into brain and non-brain has been ...
Abstract. A robust method for the removal of non-cerebral tissue in T1-weigh-ted magnetic resonance ...
The study of structural and functional magnetic resonance imaging data has greatly benefitted from t...
The segmentation of brain tissue from nonbrain tissue in magnetic resonance (MR) images, commonly re...
Segmentation of an image is most important and essential task in medical image processing, specifica...
The removal of non-brain signal from magnetic resonance imaging (MRI) data, known as skull-stripping...
This paper introduces an interactive and intelligent approach for accurate brain segmentation. A hig...
BackgroundSegmentation methods for medical images may not generalize well to new data sets or new ta...
An important area of current research is obtaining more information about brain structure and funct...
Accurate and fully automatic segmentation of brain from magnetic resonance (MR)scans is a challengin...
We present an automated method for segmenting skull, scalp, and brain regions in T1-weighted MR imag...
Accurate brain tissue extraction on magnetic resonance imaging (MRI) data is crucial for analyzing b...
Isolation of the brain from other tissue types in magnetic resonance (MR) images is an important ste...
doi: 10.3389/fninf.2013.00032 Brain extraction using the watershed transform from marker
Extraction of the brain—i.e. cerebrum, cerebellum, and brain stem—from T1-weighted structural magnet...
An automated method for segmenting magnetic resonance head images into brain and non-brain has been ...
Abstract. A robust method for the removal of non-cerebral tissue in T1-weigh-ted magnetic resonance ...
The study of structural and functional magnetic resonance imaging data has greatly benefitted from t...
The segmentation of brain tissue from nonbrain tissue in magnetic resonance (MR) images, commonly re...
Segmentation of an image is most important and essential task in medical image processing, specifica...
The removal of non-brain signal from magnetic resonance imaging (MRI) data, known as skull-stripping...
This paper introduces an interactive and intelligent approach for accurate brain segmentation. A hig...
BackgroundSegmentation methods for medical images may not generalize well to new data sets or new ta...
An important area of current research is obtaining more information about brain structure and funct...
Accurate and fully automatic segmentation of brain from magnetic resonance (MR)scans is a challengin...
We present an automated method for segmenting skull, scalp, and brain regions in T1-weighted MR imag...
Accurate brain tissue extraction on magnetic resonance imaging (MRI) data is crucial for analyzing b...