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IceImarisConnector

IceImarisConnector is a simple commodity class that eases communication between Bitplane Imaris and MATLAB or python using the Imaris XT interface.

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Balanced SOFI

Super-resolution optical fluctuation imaging (SOFI) achieves 3D super-resolution by computing temporal cumulants or spatio-temporal cross-cumulants of stochastically blinking fluorophores [1,2]. In contrast to localization microscopy, SOFI is compatible with weakly emitting fluorophores and a wider range of blinking conditions [3]. Balanced SOFI analyses several cumulant orders for extracting molecular parameter maps, such as the bright and dark state lifetimes, the concentration and the brightness distributions of fluorophores within biological samples [a].

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Detect Cells with MATLAB CellDetector

Workflow Language: 
MATLAB
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MicrobeTracker

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SimuCell

An open-source framework to synthetically generate fluorescent microscopic images of cellular population.

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GNU Octave

"GNU Octave is a high-level language, primarily intended for numerical computations."* It can also be used for image processing, statistics and plotting as well as Matlab. "GNU Octave is also freely redistributable software. You may redistribute it and/or mod- ify it under the terms of the GNU General Public License as published by the Free Software Foundation."*

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Amira

3D visualization and analysis software

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Schnitzcells

Schnitzcells is a MATLAB based software that allows for quantitative analysis of fluorescent time-lapse movies of living cells. The software package is developed most specifically for bacteria and has been instrumental in analyzing E.coli and B. subtilis movies.
The software contains functions that segment cells (based on either fluorescence or phase images),tracks cells in a frame-to-frame manner,build lineage trees and quantitatively extracts fluorescence.

dscho's picture

Matlab Computer Vision System Toolbox

The Matlab Computer Vision System Toolbox extends the Matlab core functionality with general purpose image processing functions for feature detection & extraction, object detection & tracking and motion estimation.

Strengths:
- Most functions extend to nD
- optimized functions (muti-threaded for some)
- Matlab community (Matlab central)
- relatively low entry-threshold for functionality
- Tutorials & Webinars

Limitations:
- no embedded visualization of nD Microscopy data

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