Abstract #0952

Fully Automatic Segmentation of the Amygdala on High Resolution T1 Images Using a Shape Model

Frank Thiele¹,², Lukas Scheef², Fabian Wenzel³, Carsten Meyer³, Henning Boecker², Michael Wagner⁴, Hans H. Schild², Frank Jessen⁴

¹Philips Research, Aachen, Germany; ²Radiology, University of Bonn, Bonn, Germany; ³Philips Research, Hamburg, Germany; ⁴Psychiatry, University of Bonn, Bonn, Germany

Automatic segmentation of amygdala volumes would present an important tool for neuroscience studies in cognition and psychiatry, and a potential diagnostic marker. In this work, a shape model is applied to T1-weighted MRI for fully automatic segmentation of the amygdala in 70 elderly normals. Segmentation is compared to manual tracing as well as a state-of-the-art atlas-based approach. The shape model is found to be a promising approach for reproducible and observer-independent analysis of the amygdala.