Abstract:
:The location and masking of the brain and surrounding cerebrospinal fluid (CSF) in two-dimensional (2D) dual-echo fast spin-echo (FSE) magnetic resonance (MR) images of the head is achieved by an automated procedure with a voxel-based computational algorithm. Linear scale-space features are derived from the short-echo, proton-density (PD)-weighted images. The second-order Gaussian derivative (the Laplacian) operator is applied at three different spatial scales as a measure of image convexity/concavity with a first-order Gaussian derivative measure (the squared gradient) at a single scale used to circumscribe cortical regions. A mask obtained from the long-echo, T2-weighted image is used to remove extracerebral components of the visual system. A three-dimensional (3D) connectivity analysis then identifies the largest connected volume as the brain. Five dual-echo fast spin-echo images acquired by repeated scanning of the same normal volunteer were used to verify reproducibility; and coronal and axial acquisitions from another normal volunteer to demonstrate the method's robustness to data collected with non-cubic voxels. Images acquired from five individuals with Alzheimer's disease are also presented to show that the algorithm can be used in cases of non-normative anatomy. Validity is affirmed by demonstrating that cerebral volumes estimated by this method for all 12 images are highly correlated (R = 0.98) with estimates obtained by an expert human operator.
journal_name
Magn Reson Imagingjournal_title
Magnetic resonance imagingauthors
Suckling J,Brammer MJ,Lingford-Hughes A,Bullmore ETdoi
10.1016/s0730-725x(98)00099-xsubject
Has Abstractpub_date
1999-02-01 00:00:00pages
247-56issue
2eissn
0730-725Xissn
1873-5894pii
S0730-725X(98)00099-Xjournal_volume
17pub_type
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