Journal ArticleDOI
Correction of intensity nonuniformity in MR images of any orientation.
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TLDR
Tests demonstrate that the uniformity of images of any orientation can be improved significantly with a correction matrix from just one orientation and still further with two matrices, one axial and the other either coronal or sagittal.About:
This article is published in Magnetic Resonance Imaging.The article was published on 1993-01-01. It has received 171 citations till now. The article focuses on the topics: Orientation (computer vision) & Imaging phantom.read more
Citations
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Journal ArticleDOI
A nonparametric method for automatic correction of intensity nonuniformity in MRI data
TL;DR: A novel approach to correcting for intensity nonuniformity in magnetic resonance (MR) data is described that achieves high performance without requiring a model of the tissue classes present, and is applied at an early stage in an automated data analysis, before a tissue model is available.
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A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data
TL;DR: A novel algorithm for fuzzy segmentation of magnetic resonance imaging (MRI) data and estimation of intensity inhomogeneities using fuzzy logic and the neighborhood effect acts as a regularizer and biases the solution toward piecewise-homogeneous labelings.
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A Review of Methods for Correction of Intensity Inhomogeneity in MRI
TL;DR: Several methods that have been developed to reduce or eliminate intensity inhomogeneities in MRI are reviewed, and key evaluation issues and future development of the inhomogeneity correction field are discussed.
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Automatic "pipeline" analysis of 3-D MRI data for clinical trials: application to multiple sclerosis
TL;DR: A fully automatic "pipeline" image analysis framework that enhances the ability to detect small treatment effects not readily detectable through conventional analysis techniques and holds widespread potential for applications in other neurological disorders, as well as for the study of neurobiology in general.
Journal ArticleDOI
MRI segmentation: Methods and applications
Laurence P. Clarke,R.P. Velthuizen,M.A. Camacho,John J. Heine,M. Vaidyanathan,Lawrence O. Hall,R.W. Thatcher,Martin L. Silbiger +7 more
TL;DR: The application of MRI segmentation for tumor volume measurements during the course of therapy is presented here as an example, illustrating problems associated with inter- and intra-observer variations inherent to supervised methods.
References
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Segmentation of MR brain images into cerebrospinal fluid spaces, white and gray matter.
TL;DR: An interactive computer method for quantifying CSF, white matter, and gray matter in magnetic resonance (MR) axial brain scans is presented and the gray/white ratios compare favorably with those determined in a published postmortem brain study.
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Intensity correction in surface-coil MR imaging
TL;DR: A method is reported for correcting surface-coil images so as to produce a uniform relative intensity over the region being imaged, where the local image contrast will decrease proportionally to the average local intensity.
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Adaptive filters for digital image noise smoothing: An evaluation*
TL;DR: Six adaptive noise filtering algorithms were implemented and evaluated and an adaptive filter was used iteratively with varying window sizes to demonstrate the success of iterative adaptive smoothing.
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Image non-uniformity in magnetic resonance imaging: its magnitude and methods for its correction
TL;DR: Image non-uniformity in magnetic resonance imaging (MRI) is a recognised problem when using surface coils but is rarely mentioned with respect to standard head coils, yet it can be a source of error in clinical interpretation of images.
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Quantitative evaluation of some edge-preserving noise-smoothing techniques
Roland T. Chin,Chia-Lung Yeh +1 more
TL;DR: An objective measure, the mean-square error, is obtained for each region of the partitioned image to evaluate the performance of the smoothing scheme at the corresponding level of spatial activity content.