The importance of partial voluming in multi-dimensional medical image segmentation
The presented method addresses the problem of multi-spectral image segmentation through
use of a model which takes into account partial volumes of tissues being present in a single
voxel at boundaries. The parameters of the multi-dimensional model of pure tissues and
their mixtures are iteratively adjusted using an Expectation Maximisation (EM) optimisation
technique. Bayes theory is used to generate probability maps for each segmented tissue
which estimates the most likely tissue volume fraction within each voxel.
use of a model which takes into account partial volumes of tissues being present in a single
voxel at boundaries. The parameters of the multi-dimensional model of pure tissues and
their mixtures are iteratively adjusted using an Expectation Maximisation (EM) optimisation
technique. Bayes theory is used to generate probability maps for each segmented tissue
which estimates the most likely tissue volume fraction within each voxel.
[CITATION][C] The importance of partial voluming in multi-dimensional medical image segmentation. MICCAI 2001 LNCS 2208
M Pokric, N Thacker, M Scott - 2001 - Springer-Verlag
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