Automated Approximation of Lateral Ventricular Shape in Magnetic Resonance Images of Multiple Sclerosis Patients

"Active surfaces" or deformable models have been proposed for the segmentation of anatomic structures in MRI data. Such algorithms are dependent on a good initial approximation of the target shape. The purpose of this work was to develop a reliable method for automatic generation of a starting point for segmentation of the lateral ventricle. The algorithm uses a parametric representation of an average lateral ventricle, which is customized for each individual by modulating the parametric coefficients based on the brain parenchymal fraction. The method was developed with a training set of 6 healthy controls and 25 patients with multiple sclerosis, and tested on an additional set of 10 patients. Compared to the average ventricle, this new approach provided a closer approximation to the manually segmented ventricular shape in 81% of the cases in the training set and 100% of the additional test set.

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