Automated

Description
Plot the centroid tracks and area evolution of the cells of a tissue with membrane labelling.
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Description

The original paper describes a method to analyze mitochondrial morphology in 2D and 3D.

Description

The goal of this workflow is to track cells captured in a time-lapse movie of a syncytial blastoderm stage Drosophila embryo and quantify their movement.

This example shows an example of object tracking. This pipeline analyzes a time-lapse experiment to identify the cells and track them from frame to frame, which is challenging since the cells are also moving. In addition, this pipeline also extracts metadata from the filename and uses groups the images by metadata in order to independently process several sequences of images and output the measurements of each.

Sample images

A portion of a time lapse movie of a syncytial blastoderm stage Drosophila embryo with a GFP-histone gene which renders chromatin fluorescent in live embryos. The movie shows nuclear divisions 10 through 13.

Victoria Foe made this movie on a Bio-Rad Radiance 2000 laser scanning confocal microscope using a 40X 1.3NA oil objective. The frames are 7 seconds apart and plays at 30 frames per second

GFP-histone transformed files provided by Rob Saint

V.Foe and G.Odell, . 26 July 2001

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Description

Task

Quantify the length of microtubules (MT) and the MT average density per cell.

Workflow descriptions

Simple two step workflow, allowing visual & manual correction of microtubule between the 2 steps. Batch measurement of microtubule lengths for multiple images is achieved by segmenting the MTs and then their skeletonizations. The number of pixels in the microtubule is proportional to their length, so the length can be estimated.

Script

Workflow is written as an ImageJ macro (Fiji) with following steps:

1. The enhancement of tubular structure by computing eigenvalues of the hessian matrix on a Gaussian filtered version of the image ( sigma 1 pixel), as implemented in the tubeness plugin.

2. The tubules were then thresholded , and structures containing less than 3 pixels were discarded.

3. If needed, a visual check and correction of segmented microtubule is then performed.

4. After correction, segmented MTs were then reduced to a 1-pixel thick line using the skeletonize plugin of Fiji. The length of the skeletonized microtubules was then directly proportional to their length.

5. Data were grouped by condition and converted back to micrometers units under Matlab for the statistical tests.

Pitfalls

Commented but not that general without editing some fields in the macros.

Sample Data

Sample data and workflow (see above URL) can be accessed by - login: biii - password Biii!

Misc

3D version also available here. Use of components Skeletonize and Tubeness Filter

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Description

Analyzing ER, PR, and Ki-67 immunohistochemistry

ImmunoRatio is an ImageJ plugin to quantify haematoxylin and DAB-stained tissue sections by measuring the percentage of positively stained nuclear area (labeling index), described in [bib]2452[/bib].

Notes for use:

  • It is important to read the URL instructions and original paper to understand what is being measured. In particular, the primary measurement made is percentage of the total nuclear area, not the percentage of detected nuclei (the latter being the more common method of assessing e.g. Ki67). This may be further modified by the Result correction equation.
  • Ultimately ImmunoRatio relies on thresholding (color deconvolved [bib]2451[/bib]) images to define 'nucleus' vs 'non-nucleus' regions according to staining intensity. Therefore dark artefacts, such as tissue folds, are likely to cause errors.
  • 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).

Web application: ImmunoRatio

Example Image: Sample ImmunoRatio results

References

  1. [2452] Tuominen VJRuotoistenmäki SViitanen AJumppanen MIsola J.  2010.  ImmunoRatio: a publicly available web application for quantitative image analysis of estrogen receptor (ER), progesterone receptor (PR), and Ki-67.. Breast Cancer Res. 12(4):R56.
  2. [2451] Ruifrok ACJohnston DA.  2001.  Quantification of histochemical staining by color deconvolution.. Anal Quant Cytol Histol. 23(4):291-9.
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