GaussFit OnSpot

Description

quote: 

GaussFit_OnSpot is an ImageJ plugin for fitting Gaussian profiles onto selected positions in diffraction-limited images (e.g. single molecules, protein clusters, vesicles, or stars).

The plugin performs a function fit in regions of interest (ROI) around spots marked by point selections in grayscale images. Single or multiple spots can be either selected manually with the Multi-point tool or automatically with the Find Maxima function.

There is a PDF with more information, and also an example image.

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Spots colocalization (ComDet)

Description

Quote " finding and/or analyzing colocalization of bright intensity spots (cells, particles, vesicles, comets, dots, etc) in images with heterogeneous background (microscopy, astronomy, engineering, etc). "

Uses Gaussian-Mexican hat convolution for preprocessing.

PTA2

Description

"PTA2 is an ImageJ1.x plugins that enable automatic particle tracking"

This plugin is developed specifically for single-molecule imaging, so it's good at tracking spots with noisy background. 

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MiToBo

Description

"The Microscope Image Analysis Toolbox MiToBo is an extension for the widely used image processing application ImageJ and its new release ImageJ 2.0.
MiToBo ships with a set of operators ready to be used as plugins in ImageJ. They focus on the analysis of biomedical images acquired by various types of microscopes."

HDomeTransform3D

Description

h-Dome transformation, useful for spot detection.

Jython code example:

from de.unihalle.informatik.MiToBo.core.datatypes.images import MTBImage
from de.unihalle.informatik.MiToBo.morphology import HDomeTransform3D
from ij import IJ

imp = IJ.getImage()
mtb = MTBImage.createMTBImage( imp.duplicate() )
hdome = HDomeTransform3D(mtb, 10.0)
hdome.runOp()
mtbdone = hdome.getResultImage()
imp2 = mtbdone.getImagePlus()
imp2.show()

Nessys

Description

Nessys: Nuclear Envelope Segmentation System

 

Nessys is a software written in Java for the automated identification of cell nuclei in biological images (3D + time). It is designed to perform well in complex samples, i.e when cells are particularly crowded and heterogeneous such as in embryos or in 3D cell cultures. Nessys is also fast and will work on large images which do not fit in memory.


Nessys also offers an interactive user interface for the curation and validation of segmentation results. Think of this as a 3D painter / editor. This editor can also be used to generate manually segmented images to use as ground truth for testing the accuracy of the automated segmentation method.


Finally Nessys, contains a utility for assessing the accuracy of the automated segmentation method. It works by comparing the result of the automated method to a manually generated ground truth. This utility will provide two types of output: a table with a number of metrics about the accuracy and an image representing a map of the mismatch between the result of the automated method and the ground truth.

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FluoRender

Description

FluoRender is an interactive rendering tool for confocal microscopy data visualization. It combines the rendering of multi-channel volume data and polygon mesh data, where the properties of each dataset can be adjusted independently and quickly. The tool is designed especially for neurobiologists, allowing them to better visualize confocal data from fluorescently-stained brains, but it is also useful for other biological samples.

FluoRenderer

3Dscript

Description

3Dscript is a plugin for Fiji/ImageJ for creating 3D and 4D animations of microscope data. In contrast to existing 3D visualization packages, animations are not keyframe-based, but are described by a natural language-based syntax.

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Labkit

Description

Labkit is an open-source tool to segment truly large image data using sparse training data. It has an intuitive and responsive user interface based on Big Data Viewer, allowing users to conveniently browse and annotate even terabyte sized image volumes.

Update site: Labkit

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SciView

Description

SciView is an ImageJ/FIJI plugin for 3D visualization of images and meshes. It uses the Scenery and ClearVolume infrastructure. SciView integrates ImageJ2 functionality, including ImageJ Ops and ImageJ Mesh, to provide the ability to interact with image and mesh data in 3D and interface with the popular Fiji software ecosystem.

An update site is available: http://sites.imagej.net/SciView/

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