Title :
Tissue Mixture Characterization In The Presence of Mri Inhomogeneity by the Em Algorithm
Author :
Liang, Z. ; Li, L. ; Eremina, D. ; Lu, H.
Author_Institution :
Dept. of Radiol., State Univ. of New York, Stony Brook, NY
Abstract :
This paper presents a model-based approach to correct for both partial volume effect and inhomogeneity in segmenting tissue mixtures inside each voxel of magnetic resonance images. A maximum a posteriori probability (MAP) solution is sought. In calculating the solution, the well-known expectation maximization (EM) algorithm is employed. The models of data likelihood and Markov priors for tissue mixture and bias field in establishing this MAP-EM framework are described in details. A preliminary test is presented
Keywords :
Markov processes; biological tissues; biomedical MRI; expectation-maximisation algorithm; image segmentation; medical image processing; MAP; MRI inhomogeneity; Markov priors; expectation maximization algorithm; magnetic resonance images; maximum a posteriori probability; segmenting tissue mixtures; tissue mixture characterization; Biomedical engineering; Computer science; Image segmentation; Magnetic resonance; Magnetic resonance imaging; Mathematics; Numerical models; Physics; Radiology; Random variables;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on
Conference_Location :
Toulouse
Print_ISBN :
1-4244-0469-X
DOI :
10.1109/ICASSP.2006.1660549
