Abstract
Astrocytes play a critical part in the regular functioning of the central nervous system and are widely studied to better understand how the body reacts to various diseases. Hundreds of individual cells must often be analyzed to produce statistically relevant analytical data from three-dimensional (3D) microscope images of Astrocytes. As a result, having an effective mechanism for automatically analyzing these data in a way that is resistant to human bias is critical and challenging because glial cells are generally uniform and densely packed. Therefore, we present an approach that automatically processes 3D micrographs of astrocytes and generates a set of measurements that can be used to compare between different images. We conducted an experimental evaluation of our approach based on a set of images of astrocyte 3D micrographs. The initial results show that the proposed approach is potentially promising.