Neuroglancer

Description

Web based viewer developped for google for very big data: 

Neuroglancer is a WebGL-based viewer for volumetric data. It is capable of displaying arbitrary (non axis-aligned) cross-sectional views of volumetric data, as well as 3-D meshes and line-segment based models (skeletons). The segmentation has to be done before loading the dataset, it is not done Inside the viewer.

This is not an official Google product.

It has among other the nice feature of beeing able to generate url for sharing a specific view.

Note that the only supported browser for now are 

  • Chrome >= 51
  • Firefox >= 46

 

Neuroglancer

3D-Segmentation

Description

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ImageJFIJI

Description

The research goal of this paper was to provide unbiased counts of labeled astrocytes and to estimate the area they cover, further to develop tools for defining the orientation of coupling within astrocyte networks under different stimuli.

In order to count the astrocytes and estimate the area they cover the following steps were used in this software.

Pre-processing: z-project (using max intensity); split channels; subtract background; remove outliers.

Segmentation: adjust threshold and convert to a binary file; Watershed.

Cell counting: Analyze particles

Measure Astrocytic network area: select a ROI using the polygon tool; set measurements (area); ROI manager -> add the traced polygon; measure.

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WormScan

Description

We have developed WormScan, an automated image acquisition system that allows quantitative analysis of each of these four phenotypes on standard NGM plates seeded with E. coli. This system is very easy to implement and has the capacity to be used in high-throughput analysis.

Protein Array Analyzer for ImageJ

Description

Protein array is used to analyze protein expressions by screening simultaneously several protein-molecule interactions such as protein-protein and protein-DNA interactions. In most cases, the detection of interactions leads to an image containing numerous lines of spots that will be analyzed by comparing tables of intensity values. To describe the observed different patterns of expression, users generally show histograms with the original associated images [1]. The “Protein Array Analyzer” gives a friendly way to exploit this type of analysis, thus allowing quantification, image modeling and comparative analysis of patterns.

The Protein Array Analyzer, which was programmed in ImageJ’s macro language, is an extention of the Dot Blot Analyzer, [2], [3] a graphically interfaced tool that greatly simplifying analysis of dot arrays.

Multi-Template matching

Description

Multi-template matching can be used to localize multiple objects using one or a set of template images.

Contrary to previous implementations that allow to use only one template, here a set of templates can be used or the initial template(s) can be transformed by rotation/flipping.

Multiple objects detection without redundant detections is possible thanks to a Non-Maxima Supression relying on the degree of overlap between detections.

The solution is available as a Fiji plugin (Multi-Template Matching update site) and as a Python package (Multi-Template-Matching on PyPI)

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FPBioimage

Description

FPBioimage is a volumetric visualization tool which runs in all modern web browsers. Try the tool yourself at our example site here.

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PYME

Description

The PYthon Microscopy Environment is an open-source package providing image acquisition and data analysis functionality for a number of microscopy applications, but with a particular emphasis on single molecule localisation microscopy (PALM/STORM/PAINT etc ...). The package is multi platform, running on Windows, Linux, and OSX.

It comes with 3 main modules:

  • PYMEAcquire - Instrument control and simulation
  • dh5view - Image Data Analysis and Viewing
  • VisGUI - Visualising Localization Data Sets

CellProfiler Analyst CPA

Description

CellProfiler Analyst (CPA) allows interactive exploration and analysis of data, particularly from high-throughput, image-based experiments. Included is a supervised machine learning system which can be trained to recognize complicated and subtle phenotypes, for automatic scoring of millions of cells. CPA provides tools for exploring and analyzing multidimensional data, particularly data from high-throughput, image-based experiments analyzed by its companion image analysis software, CellProfiler.

CPA

Image Data Explorer

Description

The Image Data Explorer is a Shiny app that allows the interactive visualization of images and ROIs associated with data points shown in a scatter plot. It is useful for exploring the relationships between images/ROIs and associated data represented in tabular format.

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