Cell segmentation

Description

DBSCAN (Density-based spatial clustering of applications with noise) performs multi-dimensional clustering based on the local density of points. This plugin is implemented for 2-3 dimensions.

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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. 

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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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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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.