The Effects of Magnetic Resonance Image Inhomogeneities on Automated Tissue Classification

Stephen Aylward, James Coggins, Ted Cizadlo and Nancy Andreasen

Inhomogeneities in the generated and induced fields of MR systems produce nonlinear intensity distortions in the resulting MR images. Analysis presented in this paper reveals how these deformations reduce classification accuracy when only multiecho information and standard gaussian classification techniques are used. Improved tissue labeling can be achieved by augmenting feature space with spatial information and by increasing the class representation capabilities of the classifier using mixture modeling techniques.


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