NDLI: Utilizing prior information for bias field estimation and segmentation of MRI data

Content Provider	IEEE Xplore Digital Library
Author	El-Melegy, M. Mokhtar, H.
Copyright Year	2009
Description	Author affiliation: Electrical Engineering Department, Assiut University, 71516, Egypt (El-Melegy, M.; Mokhtar, H.)
Abstract	The method of utilizing available prior information in the popular FCM algorithm and assesses its benefits in estimating the intensity inhomogeneities and segmenting human brain MRI volumes is studied in this paper. The intensity inhomogeneities in medical images are associated with the acquisition sequences and imperfections in the radio-frequency coils in MRI scanners. Presence of intensity inhomogeneities in medical images produces a shading artifact which biases the true voxel intensity. The proposed method modifies the objective function of the standard FCM to take into account any available information about the class centers, and class's pixels distribution throughout the MRI volume. The experiments using 3D synthetic phantoms and real MRI volumes show that the proposed method has considerable better segmentation accuracy, robustness against noise, and needs a smaller number of iterations to reach convergence compared with other most famous reported techniques.
Starting Page	327
Ending Page	332
File Size	286943
Page Count	6
File Format	PDF
ISBN	9781424458424
DOI	10.1109/ICCES.2009.5383246
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-12-14
Publisher Place	Egypt
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Coils Nonuniform electric fields bias field Humans Fuzzy c-mean medical image segmentation Radio frequency Image segmentation Magnetic resonance imaging Intensity inhomogeneity Iterative algorithms Positron emission tomography Medical diagnostic imaging Biomedical imaging
Content Type	Text
Resource Type	Article

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