Compression, Segmentation, and Modeling of Large-Scale Filamentary Volumetric Data

We describe a method for processing large amounts of volumetric data collected from a Knife Edge Scanning Microscope (KESM). The neuronal data that we acquire consists of thin, branching structures extending over very large regions that prior volumetric representations have difficulty dealing with efficiently. Since the full volume data set can be extremely large, on-the-fly processing of the data is necessary