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Signal formulation, segmentation, and lesion volume estimation in magnetic resonance images
In this dissertation we present a new approach to estimate the volume of ischermic stroke lesions using magnetic resonance imagery (MRI). The approach is hierarchical, regularized, and guided by statistical theory, resulting in a confidence map for the lesion itself and a confidence interval for the lesion volume. We test the procedure on synthetic data and real MRI, with estimates to within 6% of the volumes from physicians' hand segmentations. These results compare favorably to those from other Bayesian-based methods. Also, we present a formulation of the free induction decay signal for several MR pulse sequences, which allow for the classification of distinct tissue types in MRI.
Stein, Benjamin Reece, "Signal formulation, segmentation, and lesion volume estimation in magnetic resonance images" (2001). Doctoral Dissertations Available from Proquest. AAI3027260.