Abstract #1778
Automated Segmentation of the Human Amygdala using High Angular Diffusion Imaging (HARDI) and Spectral k-means Clustering
Brian David Stirling 1 , Yu-Chien Wu 1 , Long Sha 1,2 , Jim Haxby 1 , and Paul J Whalen 1
1
Psychological and Brain Sciences, Dartmouth
College, Hanover, NH, United States,
2
Neuroscience
Institute, New York University, New York, NY, United
States
Despite the functional relevance and unique circuitry of
each human amygdaloid subnucleus, there has yet to be an
efficient imaging method for identifying these regions.
The present study uses High Angular Resolution Diffusion
Imaging (HARDI), high spatial resolution, and spectral
k-means clustering to segment the amygdala. Clustering
was performed on the similarity matrices generated from
the spherical harmonic (SH) coefficients of the whole
structure orientation distribution function (ODF) across
32 subjects. The results show that these methods were
able to significantly segment the amygdala into 3
distinct regions: a medial region, a
posterior-superior-lateral region, and an
anterior-inferior-lateral region.
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