Image visualisation

Visualisation vs Plotting vs Image generation. Should these be merged? Which of these should be the top concept, and which sub-concepts, and which narrow synonyms?

Synonyms
Rendering
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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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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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Description

Paintera is a general visualization tool for 3D volumetric data and proof-reading in segmentation/reconstruction with a primary focus on neuron reconstruction from electron micrographs in connectomics. It features/supports:

  •  Views of orthogonal 2D cross-sections of the data at arbitrary angles and zoom levels
  •  Mipmaps for efficient display of arbitrarily large data at arbitrary scale levels
  •  Label data
    •  Painting
    •  Manual agglomeration
    •  3D visualization as polygon meshes
      •  Meshes for each mipmap level
      •  Mesh generation on-the-fly via marching cubes to incorporate painted labels and agglomerations in 3D visualization. Marching Cubes is parallelized over small blocks. Only relevant blocks are considered (huge speed-up for sparse label data).

Paintera is implemented in Java and makes extensive use of the UI framework JavaFX

Paintera screenshot
Description

shinyHTM is an open source, web-based tool for data exploration, image visualization and normalization of High Throughput Microscopy data. Within shinyHTM the user is guided through a linear workflow which follows the following best practices:

  • Inspect the numerical data through plotting
  • Measurements are linked to raw images
  • Perform quality control to exclude images with aberrations or where image analysis failed
  • Perform a reproducible data analysis
  • Normalize data and report statistical significance

Image visualization relies on Fiji/ImageJ, along with its wealth of analytical tools.

shinyHTM can be used to analyze image features obtained with CellProfiler, ImageJ or any other bioimage analysis software. The output of analysis is a publication-ready scoring of the data.

shinyHTM is based on the R shiny package.

shinyHTM
Description

ParaView is an open-source, multi-platform data analysis and visualization application. ParaView users can quickly build visualizations to analyze their data using qualitative and quantitative techniques. The data exploration can be done interactively in 3D or programmatically using ParaView’s batch processing capabilities.

ParaView was developed to analyze extremely large datasets using distributed memory computing resources. It can be run on supercomputers to analyze datasets of petascale size as well as on laptops for smaller data, has become an integral tool in many national laboratories, universities and industry, and has won several awards related to high performance computation.

paraviewbloodcells