Title :
Tissue segmentation of multi-channel brain images with inhomogeneity correction
Author :
Tan, Choong Leong ; Rajapakse, Jagath C.
Author_Institution :
Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore
Abstract :
We propose a novel method to segment multi-channel magnetic resonance brain images into tissue classes taking into consideration the bias fields created by in-homogeneities of the scanners. The joint probability of tissue intensities in the multi-channel image is modeled using a multivariate Gaussian function; the prior models of tissue classes are presumed to be Markov random fields. An iterative algorithm is proposed to find the maximum a posteriori estimation of segmentation; suboptimally. Experiments on simultaneously acquired proton-density and T2-weighted images are demonstrated.
Keywords :
Gaussian processes; Markov processes; biomedical MRI; brain; image segmentation; maximum likelihood estimation; medical image processing; inhomogeneity correction; multichannel magnetic resonance brain images; multivariate Gaussian function; tissue segmentation; Brain; Image analysis; Image segmentation; Iterative algorithms; Magnetic resonance; Magnetic resonance imaging; Markov random fields; Protons; Senior members; Student members;
Conference_Titel :
Image and Signal Processing and Analysis, 2003. ISPA 2003. Proceedings of the 3rd International Symposium on
Print_ISBN :
953-184-061-X
DOI :
10.1109/ISPA.2003.1296961