tischi / imagej-open-stacks-as-virtualstack

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imagej-open-stacks-as-virtualstack

Functionality

This ImageJ plugin suite constructs a virtual stack (data stream) from a folder of image stacks. This is useful for large (~1TB) data sets as typically acquired with light-sheet microscopy. In addition to viewing the data it also allows you to track objects in the data set in an efficient and fast manner; it is efficient, because it only loads the data around the tracked objects and it is fast, because the code is optimised for speed and uses multi-threading.

Plugin help

Below pages summarise the information that you get by hovering with the mouse over the respective button in each plugin.

Data Streaming Tools

Track and Crop

Usage notes

The folder structure of your input data currently must consist of one main folder containing subfolders for each channel, where each of the channel subfolders contains the image stacks representing the time-points. The names of the folders and files are arbitrary, they are only used to sort the channels and time-points (the sorted file lists will be printed in the IJ log window; please check that the order is correct!).

When you stream from the main folder the first time, the plugin will analyse all files. This can take some time, especially when the image data is saved as tif stacks.

Supported file formats

This plugin currently only supports a few file formats; it was tested for

Installation in Fiji

  1. Download the jar: https://github.com/tischi/imagej-open-stacks-as-virtualstack/raw/master/OpenStacksAsVirtualStack_.jar
  2. Move OpenStacksAsVirtualStack_.jar into your Fiji.app/plugins.

Installation in ImageJ

  1. Download https://github.com/tischi/imagej-open-stacks-as-virtualstack/raw/master/OpenStacksAsVirtualStack_.jar
  2. Download the whole repository and copy the .jar files in the open_stacks_as_virtual_stack_maven/lib/ folder into the plugins/jars folder of ImageJ

Usage instructions

Data streaming

  1. Run: [Plugins > ALMF SPIM > Data Streaming Tools]
  2. [Stream from folder]: Streams the image data from the folder into IJ's hyperstack viewer

Tracking

  1. Run: [Plugins > ALMF SPIM > Big Data Tracker]
  2. ...