George
Iordanescu1,2, Palamadai Venkatasubramanian1,2, Alice
Wyrwicz1,3
1Center for Basic MR Research,
Northshore University HealthSystem, Evanston, IL, United States; 2Pritzker
School of Medicine, University of Chicago, Chicago, IL, United States; 3Biomedical
Engineering, Northwestern University, Evanston, IL, United States
Loss
of neurons and synapses is a key features that characterize Alzheimers
disease (AD). A novel semi-automatic segmentation method is used to quantify
the neuronal loss in the pyramidal cell layer in hippocampal CA1 subfield
(PLCA1) in a very rapid progression AD model. The proposed method uses
unsupervised support vector machines. The resulting distance to the
classification hyperplane combines all classification features and measures
the neuronal cell loss as indicated by the MR contrast. The distribution of
the neuronal cell loss within the PLCA1 may be a useful tool to understand
the mechanism of cell loss in AD.