Title :
Estimating gain fields in multispectral MRI
Author :
Roozbahani, Reza Golparvar ; Ghassemian, Mohammad-Hassan ; Sharafat, Ahmad-Reza
Author_Institution :
Dept. of Electr. Eng., Tarbiat Modarres Univ., Tehran, Iran
fDate :
12/1/2000 12:00:00 AM
Abstract :
An unsupervised, completely automatic method for gain field estimation and segmentation of multispectral magnetic resonance (MR) images is presented. This new adaptive algorithm is based on statistical modeling of MR images using finite mixtures. Variability of gain field artifact with imaging parameters (i.e. TE, TR, and TI) is considered in the estimation process. Beside gain field, partial volume artifact is also considered in the labeling phase. Quantitative analysis on experimental results shows an efficient and robust performance of the adaptive algorithm and that it outperforms even advanced nonadaptive intensity-based approaches.
Keywords :
biomedical MRI; image segmentation; medical image processing; adaptive algorithm; advanced nonadaptive intensity-based approaches; gain field estimation; gain fields estimation; magnetic resonance imaging; medical diagnostic imaging; multispectral MRI; multispectral magnetic resonance images; unsupervised completely automatic method; Adaptive algorithm; Additive noise; Algorithm design and analysis; Coils; Image segmentation; Labeling; Magnetic resonance; Magnetic resonance imaging; Performance analysis; Tellurium;
Journal_Title :
Biomedical Engineering, IEEE Transactions on