Semi-Automated Routines for Functional Image Analysis (SARFIA)
SARFIA has been developed for the analysis of functional fluorescence data, for instance recordings from cells labeled with fluorescent calcium indicators. However, it allows access to a variety of inbuilt and custom-written image processing functions.
Key features are image-based detection of structures of interest using the Laplace operator, determining the positions of units in a layered network, clustering algorithms to classify units with similar functional responses, and a database to store, exchange and analyse results across experiments. GUI access to a wide range of analysis functions for image stacks.
The custom image processing functions include thresholding based on the Laplace operator, filtering of 3D waves using principal component analysis (PCA), rotating functions, images/image stacks without interpolation, line scan analysis; Automated baseline detection, hierarchical clustering and bleach subtraction from fluorescence traces.
The package includes a manual describing the control panels and a help file that describes all functions in detail.
A scientific paper based on SARFIA has been published in J Neurosci Meth (2010) 188(1):141-50. Please cite this paper when publishing data analysed in SARFIA.
|IGOR.6.12.x-1.05||2010-Dec-30||6.04 MB||Recommended for Igor 6.12.x and above||Help|