Mac

Description

The Fiji distribution of ImageJ comes with several manual tracking tools, two of which are particularly useful:

* _Plugins->Tracking->Manual Tracking_

* _Plugins->Tracking->Manual tracking with TrackMate_ (TrackMate is an advanced automatic tracking tool, with the option for manual editing of tracks)

The _Manual Tracking_ plugin is quick to use, intuitive and produces easy-to-understand output. TrackMate has the advantage that automatic detection and linkage can be combined with manual input.

Update sites

MtrackJ (see the component page here) can be installed via Fiji update sites. It has many shortcut keys enabled so for manually tracking many data, it will become quite efficient as you get used to the short-cut key operation.

Pre-processing

Pre-processing steps before manual tracking might include:

* denoising and/or deconvolution

* flicker and photobleaching correction, e.g. using Fiji's _Image->Adjust->Bleach Correction_

* flat-field correction, and/or bandpass (ImageJ's _Process->FFT->Bandpass filter_) according to the size of the features of interest

has function
Description

Image processing library for Python >The scikit-image SciKit (toolkit for SciPy) extends scipy.ndimage to provide a versatile set of image processing routines. It is written in the Python language. This SciKit is developed by the SciPy community. All contributions are most welcome!

has function
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Description

This protocol takes a folder containing images as input and extract each channel in a separate sub folder.

need a thumbnail
Description

This method allows to compute a threshold that preserves the moments of an image. In ImageJ/Fiji, you can access it in Image->Ajust->Threshold and choose Moments in the list. In Aphelion, the tool is in Segmentation->Threshold->AphImgMomentThreshold The original paper is 2449

need a thumbnail
Description

The QuimP software from Bretschneider group is deployed as ImageJ plugin and includes model-based cell segmentation, cell outline tracking and quantification of the spatially resolved speed of protrusions and retractions. The algorithm to calculate morphological dynamics is faster compared to other approaches (e.g. Machacek and Danuser, 2006). The reference paper describes the workflow for these analyses.