  The hippocampus is a seminal structure in the most common surgically-treated
form of epilepsy. Accurate segmentation of the hippocampus aids in establishing
asymmetry regarding size and signal characteristics in order to disclose the
likely site of epileptogenicity. With sufficient refinement, it may ultimately
aid in the avoidance of invasive monitoring with its expense and risk for the
patient. To this end, a reliable and consistent method for segmentation of the
hippocampus from magnetic resonance imaging (MRI) is needed. In this work, we
present a systematic and statistical analysis approach for evaluation of
automated segmentation methods in order to establish one that reliably
approximates the results achieved by manual tracing of the hippocampus.
