Fast algorithm for calculation of inhomogeneity gradient in magnetic resonance imaging data

Purpose To develop and implement a new approach for correcting the intensity inhomogeneity in magnetic resonance imaging (MRI) data. Materials and Methods The algorithm is based on the assumption that intensity inhomogeneity in MR data is multiplicative and smoothly varying. Using a statistically st...

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Bibliographic Details
Published in:Journal of magnetic resonance imaging 2010-11, Vol.32 (5), p.1197-1208
Main Authors: Hui, Cheukkai, Zhou, Yu Xiang, Narayana, Ponnada
Format: Article
Language:English
Subjects:
Algorithms
Animals
bias field
Brain - anatomy & histology
Computer Simulation
Humans
Image Processing, Computer-Assisted
intensity gradient
intensity inhomogeneity
Magnetic Resonance Imaging - methods
MRI
Rats
surface-fitting
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Summary:Purpose To develop and implement a new approach for correcting the intensity inhomogeneity in magnetic resonance imaging (MRI) data. Materials and Methods The algorithm is based on the assumption that intensity inhomogeneity in MR data is multiplicative and smoothly varying. Using a statistically stable method, the algorithm first calculates the partial derivative of the inhomogeneity gradient across the data. The algorithm then solves for the gradient field and fits it to a parametric surface. It was tested on both simulated and real human and animal MRI data. Results The algorithm is shown to restore the homogeneity in all images that were tested. On real human brain images the algorithm demonstrated superior or comparable performance relative to some of the commonly used intensity inhomogeneity correction methods such as SPM, BrainSuite, and N3. Conclusion The proposed algorithm provides an alternative method for correcting the intensity inhomogeneity in MR images. It is shown to be fast and its performance is superior or comparable to algorithms described in the published literature. Due to its generality, this algorithm is applicable to MR images of both humans and animals. J. Magn. Reson. Imaging 2010;32:1197–1208. © 2010 Wiley‐Liss, Inc.
ISSN:1053-1807
1522-2586
DOI:10.1002/jmri.22344