Data handling

Description

Machine Learning made easy

APEER ML provides an easy way to train your own machine learning
models and segment your microscopy images. No expertise or coding required.

APEER

Description

webKnossos is an open-source data sharing and annotation platform for tera-scale 2D and 3D image datasets.

The core features of webKnossos are:

  • fast 3D data streaming
  • share links to specific locations in the data
  • uniquely fast skeleton annotation (flight mode) and
  • efficient volume annotation
  • mesh rendering
  • collaboration and sharing tools

webKnossos facilitates image analysis workflows on multi-terabyte datasets, including visualization of raw and multi-modal microscopy data, distributed training data generation and proof-reading of automatic segmentation.

As a scientific resource, webknossos.org serves as a database for published image datasets including their annotations.

 

 

Description

The library contains several helper functions to generate MoBIE project folders and add data to it.  Itis a python library to generate data in the MoBIE data storage layout. 

For further information, look to http://biii.eu/mobie-fiji-viewer

has function
need a thumbnail
Description

The ImageM application proposes an integrated user interface that facilitates the processing and the analysis of multi-dimensional images within the Matlab environment. It provides a user-friendly visualization of multi-dimensional images, a collection of image processing algorithms and methods for analysis of images, the management of spatial calibration, and facilities for the analysis of multi-variate images. Its graphical user interface is largely inspired from the open source software "ImageJ". ImageM can also be run on the open source alternative software to Matlab, Octave.

ImageM is freely distributed on GitHub: https://github.com/mattools/ImageM.

Processing of a 3D image with the ImageM sotfware
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