Java

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/

NanoJ-SQUIRREL (Super-resolution Quantitative Image Rating and Reporting of Error Locations) is a software package designed for assessing and mapping errors and artefacts within super-resolution images. This is achieved through quantitative comparison with a reference image of the same structure (typically a widefield, TIRF or confocal image). SQUIRREL produces quantitative maps of image quality and resolution as well as global image quality metrics.

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

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.

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.