plugin

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

Marker-controlled Watershed is an ImageJ/Fiji plugin to segment grayscale images of any type (8, 16 and 32-bit) in 2D and 3D based on the marker-controlled watershed algorithm (Meyer and Beucher, 1990). This algorithm considers the input image as a topographic surface (where higher pixel values mean higher altitude) and simulates its flooding from specific seed points or markers. A common choice for the markers are the local minima of the gradient of the image, but the method works on any specific marker, either selected manually by the user or determined automatically by another algorithm. Marker-controlled Watershed needs at least two images to run: The Input image: a 2D or 3D grayscale image to flood, usually the gradient of an image. The Marker image: an image of the same dimensions as the input containing the seed points or markers as connected regions of voxels, each of them with a different label. They correspond usually to the local minima of the input image, but they can be set arbitrarily. And it can optionally admit a third image: The Mask image: a binary image of the same dimensions as input and marker which can be used to restrict the areas of application of the algorithm. Set to "None" to run the method on the whole input image. Rest of parameters: Calculate dams: select to enable the calculation of watershed lines. Use diagonal connectivity: select to allow the flooding in diagonal directions.

Morphological Segmentation is an ImageJ/Fiji plugin that combines morphological operations, such as extended minima and morphological gradient, with watershed flooding algorithms to segment grayscale images of any type (8, 16 and 32-bit) in 2D and 3D. Morphological Segmentation runs on any open grayscale image, single 2D image or (3D) stack. If no image is open when calling the plugin, an Open dialog will pop up. The user can pan, zoom in and out, or scroll between slices (if the input image is a stack) in the main canvas as if it were any other ImageJ window. On the left side of the canvas there are three panels of parameters, one for the input image, one with the watershed parameters and one for the output options. All buttons, checkboxes and input panels contain a short explanation of their functionality that is displayed when the cursor lingers over them. Image pre-processing: some pre-processing is included in the plugin to facilitate the segmentation task. However, other pre-preprocessing may be required depending on the input image. It is up to the user to decide what filtering may be most appropriate upstream.

This macro and plugins suite for ImageJ (and Fiji) serves to measure the velocity of moving structures and visualize them, from image time series (2D over time).

The module can be installed in ImageJ as a Macro Menu and each function/component can be called separately. The full workflow consists in calling some, or all, the functions sequentially in order to get from the image preparation (e.g. filtering and visualization of tracks) to the production of the kymographs (time vs. distance plot) and their analysis (retrieving the velocities).

Here is the full workflow sequence:

• Load image sequence
• Crop and time-filter the image sequence ("Walking average" plugin)
• Generate tracks by z-projection ("Stack difference" plugin)
• Select tracks and restore them in the original stack.
• execute plugin "multiple kymograph"
• Analyse: select edges of moving tracks graphically and quantify movement in a table.

input: 8-bit, 16-bit stacks, 2D in time. Calibrated is better for meaningful velocity measurements.

ouput: the kymograph image, the velocity measurements tables.

Requires ImageJ version: 1.33.n minimum.

Example of applications:

• velocity of moving objects/ structures with sharp edges, incl. the velocity of microtubules (and their plus ends),
• the velocity of vesicles or particles along a 2D path
• the velocity of migration of the edge of a cell or a multicellular group
• retraction velocity of contractile bundles (e.g. actin fibers) or multicellular tissues after mechanical disruption (e.g. laser surgery)

An ActionBar is a simple annotated text document that has snippets of Imagej macros or Beanshell arranged into buttons. This tool is very useful when creating custom work flows integrating multiple components. Each component can be linked to a button for a more streamlined and accessible workflow.