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Correction of differential intensity inhomogeneity in longitudinal MR images.
- Source :
-
NeuroImage [Neuroimage] 2004 Sep; Vol. 23 (1), pp. 75-83. - Publication Year :
- 2004
-
Abstract
- Longitudinal MR imaging is increasingly being used to measure cerebral atrophy progression in dementia and other neurological disorders. Differences in intensity inhomogeneity between serial scans can confound these measurements. This differential bias also distorts nonlinear registration and makes both manual and automated segmentation of tissue type less reliable. A technique is described for the correction of this differential bias that makes no assumptions about signal distribution, bias field or signal homogeneity. Instead, the bias field calculation is performed on the basis that the remaining structure in the difference image of registered serial scans has small-scale structure. The differential bias field is of much larger scale and can thus be obtained by applying an appropriate filter to the difference image. The serial scan pair is then corrected for the differential bias field and atrophy measurement can be performed on the corrected scan pair. Application of a known, simulated bias field to real serial MR images was shown to alter atrophy measurements significantly. The differential correction method recovered the applied differential bias field and thereby improved atrophy measurements. This method was then applied to serial imaging in patients with dementia using a set of serial scan pairs with visually identified, significant differential bias and a set of scan pairs with negligible differential bias. Differential bias correction specifically reduced the variance of the atrophy measure significantly for the scans with significant differential bias.
- Subjects :
- Algorithms
Alzheimer Disease pathology
Analysis of Variance
Artifacts
Atrophy
Bias
Cerebellum pathology
Cerebral Ventricles pathology
Computer Simulation
Humans
Reference Values
Alzheimer Disease diagnosis
Brain pathology
Image Enhancement
Image Processing, Computer-Assisted statistics & numerical data
Magnetic Resonance Imaging statistics & numerical data
Subjects
Details
- Language :
- English
- ISSN :
- 1053-8119
- Volume :
- 23
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- NeuroImage
- Publication Type :
- Academic Journal
- Accession number :
- 15325354
- Full Text :
- https://doi.org/10.1016/j.neuroimage.2004.04.030