Automated three-dimensional detection and shape classification of dendritic spines from fluorescence microscopy images.

ABSTRACT: A fundamental challenge in understanding how dendritic spine morphology controls learning and memory has been quantifying three-dimensional (3D) spine shapes with sufficient precision to distinguish morphologic types, and sufficient throughput for robust statistical analysis. The necessity to analyze large volumetric data sets accurately, efficiently, and in true 3D has been a major bottleneck in deriving reliable relationships between altered neuronal function and changes in spine morphology. We introduce a novel system for automated detection, shape analysis and classification of dendritic spines from laser scanning microscopy (LSM) images that directly addresses these limitations. The system is more accurate, and at least an order of magnitude faster, than existing technologies. By oper

SUBMITTER: Rodriguez A 

PROVIDER: S-EPMC2292261 | biostudies-literature | 2008 Apr

REPOSITORIES: biostudies-literature