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Abstract #3752

Automated Multi-Atlas Segmentation of Anatomical Brain MR Images from Elderly Subjects.

MAGNA25Aikaterini Kotrotsou1, Niranjini Rajendran2, David A. Bennett2, Konstantinos Arfanakis1, 2

1Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, United States; 2Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, United States

An increasing number of studies use brain MRI to assess volumetric changes due to neurodegenerative diseases in the elderly. Crucial to these studies is segmentation of anatomical brain MRI data. Multi-atlas segmentation is one of the approaches used for automated labeling; however the performance of this method in subjects with age-related atrophy has not been thoroughly investigated. In this work, the performance of multi-atlas segmentation in data from elderly subjects (>80 years of age) was compared to that of FreeSurfer. It was demonstrated that multi-atlas segmentation provides results that are similar to those of FreeSurfer, in a fully automated manner.