Adiposoft

Description

Adiposoft is an automated Open Source software for the analysis of adipose tissue cellularity in histological sections.

Example data can be found on the plugin description page in ImageJ wiki (download link). There is also a link to a MATLAB version of the workflow.

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Cell segmentation in phase contrast images

Description

This Matlab code demonstrates an edge-based active contour model as an application of the Distance Regularized Level Set Evolution (DRLSE) formulation.

initialisation

Segmentation of Clustered Cells in MATLAB

Description

A clear tutorial on how to write a MATLAB script to segment clustered cells.

The full script is downloadable near the bottom of the article. 

MATLAB CellDetector

Description

CellDetector can detect cells (or other objects) in microscopy images such as histopathology, fluorescence, phase contrast, bright field, etc. It uses a machine learning-based method where a cell model is learned from simple dot annotations on a few images for training and predict on test sets. The installation requires some efforts but the instruction is well explained. Training parameters should be tuned for different datasets, but the default settings could be a good starting point.

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ImmunoMembrane

Description

Quantification of HER2 immunohistochemistry.

ImmunoMembrane is an ImageJ plugin for assessing HER2 immunohistochemistry, described in [bib]2472[/bib]. It is important to read the URL documentation and original paper to understand how to use the plugin appropriately.

There is web service available. Users can upload image data to process them and get cell membrane to be segmented: Web ImmunoMembrane

Note also that the pixel size is not read automatically from the image, but rather the source image scale should be entered into the dialog box - and the image rescaled accordingly prior to analysis. This scale value is the inverse of the value normally found for pixel width and pixel height under Image -> Properties... (i.e. pixel width & height are given in microns per pixel; the dialog box asks for pixels per micron).

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2D cell tracking and analysis of morphological dynamics

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.

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Oufti

Description

Oufti (previously named MicrobeTracker) is a MATLAB application / suite of tools for analysing fluorescent spots inside microbes. MicrobeTracker can identify cell outlines and fluorescent foci, and generate plots and statistics based on positions and intensity (kymographs, histograms etc.) The MATLAB code is easy to modify and extend to add additional plots and statistics: see e.g. Lesterlin et al. (2014).

The Outfi Forum is quite active.

Find cells using nuclear and membrane fluorescence

Description

This protocol first extracts the cell nuclei from a given fluorescence channel (full labeling), and grows a contour from each nucleus to extract the cell edge in another fluorescence channel (membrane-labeling).

Counting Clumped Cells

Description

A workflow combining ImageJ macro and manually using Trainable Weka Segmentation plugin for counting clumped cells.

Golgi Segmentation by Active Mask framework

Description

Segmentation of Golgi.

Sample Images: Link

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