|test name traning material||Training Material||
|03/01/2019 - 18:04|
|02/06/2019 - 22:18|
|rmwfONtestsite||Software||Workflow||02/03/2019 - 17:48|
|Creating an ImageJ plugin / command||Software||Workflow||
The best way to start writing an ImageJ2 plugin (ImageJ2 developers call it command and not plugin) is to download the example command from github and modify it. There is a video tutorial on the whole workflow on how to do this on youtube.
|10/18/2018 - 15:34|
|Jython for ImageJ||Software||10/18/2018 - 15:20|
|Eclipse||Software||10/18/2018 - 15:17|
|IntelliJ||Software||10/18/2018 - 15:17|
|sklearn||Software||10/18/2018 - 12:29|
|3-D Density Kernel Estimation||Software||Workflow||
3-D density kernel estimation (DKE-3-D) method, utilises an ensemble of random decision trees for counting objects in 3D images. DKE-3-D avoids the problem of discrete object identification and segmentation, common to many existing 3-D counting techniques, and outperforms other methods when quantification of densely packed and heterogeneous objects is desired.
|10/18/2018 - 12:29|
|Microscope autopilot||Software||Collection, Component||
AutoPilot is the open source project that hosts the general algorithm for fast and robust assessment of local image quality, an automated computational method for image-based mapping of the three-dimensional light-sheet geometry inside a fluorescently labeled biological specimen, and a general algorithm for data-driven optimization of the system state of light-sheet microscopes capable of multi-color imaging with multiple illumination and detection arms.
|10/18/2018 - 15:16|
|ImageJ1 - ImageJ2 transition cheat sheet||Training Material||
This cheat sheet contains pairs of code snippets explaining how to transform existing code from running in ImageJ1 to ImageJ2.
|10/18/2018 - 15:17|
|Simultaneous ImageJ script and plugin development||Training Material||
A short tutorial on how to develop, deploy and run ImageJ/Fiji scripts and Java plugins within your IDE simultaneously
|10/18/2018 - 15:20|
|Minimum cost Z surface projection||Software||Component||
This plugin detects a minimum cost z-surface in a 3D volume. A z surface is a topographic map indicating the altitude z as a function of the position (x,y) in the image. The cost of the surface depends on pixel intensity the surface is going through. This plugin find the z-surface with the lowest intensity in an image.
|10/18/2018 - 15:16|
The interactive Watershed Fiji plugin provides an interactive way to explore local maxima and threshold values while a resulting label map is updated on the fly.
After the user has found a reliable parameter configuration, it is possible to apply the same parameters to other images in a headless mode, for example via ImageJ macro scripting.
|10/18/2018 - 11:07|
|Jupyter notebook||Software||10/18/2018 - 10:44|
|Jupyter||Software||10/18/2018 - 10:44|
|NEUBIAS TS1||Training Material||04/08/2019 - 11:41|
|ImageJ/FIJI||Software||10/17/2018 - 19:50|
|Find Maxima (Python)||Software||Workflow||
Maxima finding algorithm recreated from implementation in Fiji(ImageJ)
This is a re-implementation of the java plugin written by Michael Schmid and Wayne Rasband for ImageJ. The original java code source can be found in: https://imagej.nih.gov/ij/developer/source/ij/plugin/filter/MaximumFinder.java.html
|10/18/2018 - 10:50|
|Introduction to ImageJ macro language||Training Material||
In this session, we will cover the basics of ImageJ macro programming using a simple example: how to quantify signal enrichment at the nuclear rim? Trainees will (re)discover how to record actions, plan a workflow and organise their code. This session will alternate presentation of technical points, to be directly applied during practical exercises. The macro will progressively complexify as new notions are taught.
|04/08/2019 - 11:43|