Automatic and Manual Segmentation of Hippocampus in Epileptic Patients MRI
This work addresses the need for accurate and consistent hippocampus segmentation in epilepsy patients to potentially reduce invasive monitoring, but it appears incremental as it focuses on evaluating existing automated methods rather than introducing a new one.
The paper tackled the problem of segmenting the hippocampus in MRI scans of epileptic patients to identify asymmetry for surgical planning, and it presented a systematic analysis to find an automated method that reliably matches manual tracing results.
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.