Journal article
Image background inhomogeneity correction in MRI via intensity standardization
Computerized medical imaging and graphics, Vol.33(1), pp.7-16
2009
DOI: 10.1016/j.compmedimag.2008.09.004
PMCID: PMC2656941
PMID: 19004616
Abstract
An automatic, simple, and image intensity standardization-based strategy for correcting background inhomogeneity in MR images is presented in this paper. Image intensities are first transformed to a standard intensity gray scale by a standardization process. Different tissue sample regions are then obtained from the standardized image by simply thresholding based on fixed intensity intervals. For each tissue region, a polynomial is fitted to the estimated discrete background intensity variation. Finally, a combined polynomial is determined and used for correcting the intensity inhomogeneity in the whole image. The above procedure is repeated on the corrected image iteratively until the size of the extracted tissue regions does not change significantly in two successive iterations. Intensity scale standardization is effected to make sure that the corrected image is not biased by the fitting strategy. The method has been tested on a number of simulated and clinical MR images. These tests and a comparison with the method of non-parametric non-uniform intensity normalization (
N
3
) indicate that the method is effective in background intensity inhomogeneity correction and may have a slight edge over the
N
3
method.
Details
- Title: Subtitle
- Image background inhomogeneity correction in MRI via intensity standardization
- Creators
- Ying Zhuge - Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Fourth Floor, Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104-6021, United StatesJayaram K Udupa - Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Fourth Floor, Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104-6021, United StatesJiamin Liu - Diagnostic Radiology Department, Warrent Grant Magnuson Clinical Center, National Institutes of Health, Bethesda, MD 20892, United StatesPunam K Saha - Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA 52242, United States
- Resource Type
- Journal article
- Publication Details
- Computerized medical imaging and graphics, Vol.33(1), pp.7-16
- DOI
- 10.1016/j.compmedimag.2008.09.004
- PMID
- 19004616
- PMCID
- PMC2656941
- NLM abbreviation
- Comput Med Imaging Graph
- ISSN
- 0895-6111
- eISSN
- 1879-0771
- Publisher
- Elsevier Ltd
- Language
- English
- Date published
- 2009
- Academic Unit
- Radiology; Electrical and Computer Engineering
- Record Identifier
- 9984051885802771
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