SIMA: sequential image analysis

Release:0.3.2 Date:January 15, 2015 Email:software@losonczylab.org Forum:https://groups.google.com/forum/#!forum/sima-users GitHub:https://github.com/losonczylab/sima

Overview

SIMA (Sequential IMage Analysis) is an Open Source package for analysis of time-series imaging data arising from fluorescence microscopy. The functionality of this package includes:

• correction of motion artifacts
• segmentation of imaging fields into regions of interest (ROIs)
• extraction of dynamic signals from ROIs

The included ROI Buddy software provides a graphical user interface (GUI) supporting the following functionality:

• manual creation of ROIs
• editing of ROIs resulting from automated segmentation
• registration of ROIs across separate imaging sessions

Documenation

• Installation
  • Introduction
  • Prerequisites
  • SIMA installation
• Tutorial
  • Importing SIMA
  • Example data
  • Creating an ImagingDataset object
  • Loading ImagingDataset objects
  • Motion correction
  • Segmentation and ROIs
  • Extraction
  • Exporting data
  • Complete example
• SIMA API
  • ImagingDataset objects
  • Motion correction
  • Segmentation
  • Regions of Interest (ROIs)
  • Signal extraction
• ROI Buddy GUI
  • Introduction
  • Installation
  • User Interface
  • Keyboard shortcuts
• Publications
  • Publications about SIMA
  • Research using SIMA
• Credits
  • Development
  • Testing
  • External code
  • Funding
• How you can help
  • Contact us
  • Spread the word
  • Improve the software

Citing SIMA

If you use SIMA for your research, please cite the following paper in any resulting publications:

Kaifosh P, Zaremba JD, Danielson NB, and Losonczy A. SIMA: Python software for analysis of dynamic fluorescence imaging data. Frontiers in Neuroinformatics. 2014 Aug 27; 8:77. doi: 10.3389/fninf.2014.00077.

Indices and tables

• Index
• Module Index
• Search Page