Bioimage informatics

Nuget package for conversion between color spaces and calculation of color differences. Color spaces available: -CMY -CMYK -HSL -HSB -HSV -CIE L*a*b* -Hunter LAB -L*C*h* -L*u*v* -RGB -XYZ -YXY Color differences available: -CIE76 -CMC l:c -CIE94 -CIE2000. Online example at http://colormine.org/color-converter

The jicbioimage Python package makes it easy to explore microscopy data in a programmatic fashion (python).

Exploring images via coding means that the exploratory work becomes recorded and reproducible.

Furthermore, it makes it easier to convert the exploratory work into (semi) automated analysis work flows.

Features:

• Built in functionality for working with microscopy data
• Automatic generation of audit trails
• Python integration Works with Python 2.7, 3.3 and 3.4

TurtleSeg is an interactive 3D image segmentation tool. TurtleSeg has an automated system, Spotlight, for automatically directing the user towards the next steps. Typically, a user loads a 3D image and then manually contour a sparse number of slices, the full 3D segmentation can then be built automatically.

A resident function in ImageJ, located in the menu as [Process > Binary > Voronoi].

Quote from the ImageJ reference page:

Splits the image by lines of points having equal distance to the borders of the two nearest particles. Thus, the Voronoi cell of each particle includes all points that are nearer to this particle than any other particle. When particles are single points, this process is a Voronoi tessellation (also known as Dirichlet tessellation). The output type (Overwrite, 8-bit, 16-bit or 32-bit) of this command can be set in the [Process > Binary > Options...] dialog box. In the output, the value inside the Voronoi cells is zero; the pixel values of the dividing lines between the cells are equal to the distance between the two nearest particles. This is similar to a medial axis transform of the background, but there are no lines in inner holes of particles.