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Abstract #0053

Automatic Computational Method for the Measurement of Neuronal Cell Loss in Transgenic Mouse Model of AD

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.