3D

Microscopy Image Browser (MIB) is a high-performance Matlab-based software package for advanced image processing, segmentation and visualization of multi-dimensional (2D-4D) light and electron microscopy datasets.

MIB is a freely available, user-friendly software for effective image processing of multidimensional datasets that improves and facilitates the full utilization of acquired data and enables quantitative analysis of morphological features. Its open-source environment enables fine tuning and possibility of adding new plug-ins to customize the program for specific needs of any research project.

This plugin tags all pixel/voxels in a skeleton image and then counts all its junctions, triple and quadruple points and branches, and measures their average and maximum length.

Tags are shown in a new window displaying every tag in a different color. You can find it under [Plugins>Skeleton>Analyze Skeleton (2D/3D)]. See Skeletonize3D for an example of how to produce skeleton images.

The voxels are classified into three different categories depending on their 26 neighbors: - End-point voxels: if they have less than 2 neighbors. - Junction voxels: if they have more than 2 neighbors. - Slab voxels: if they have exactly 2 neighbors.

End-point voxels are displayed in blue, slab voxels in orange and junction voxels in purple.

Notice here that, following this notation, the number of junction voxels can be different from the number of actual junctions since some junction voxels can be neighbors of each other.

Output data type: table result, image of the skeleton

MorphoGraphX is a free Linux application for the visualization and analysis of 3D biological datasets. Developed by researchers, it is primarily used for the analysis and quantification of 3D live-imaged confocal data sets.

The main research interests adressed by MorphoGraphX are:

• Shape extraction
• Growth analysis
• Signal quantification
• Protein localization

This plugin achieves easy creation of image figures for publications, reports, projects.

• Easy-to-design interactive figure layout.

• Visually assign image content to panels.

• High-quality image scaling and rotation.

• Easy and consistent panel labels and scale bars.

• Each panel has it's original datasource's properties and tracks achieved image processing.

• Save and re-open editable figures.

• Export as standard image formats with textual description of each panel history.

Compared to Make montage, the plugin adds more flexibility to montage creation: Easy-to-design interactive figure layout. Visually assign image content to panels. High-quality image scaling and rotation. Easy and consistent panel labels and scale bars. Each panel has it's original data source's properties and tracks achieved image processing. Save and re-open editable figures. Export as standard image formats with textual description of each panel history. 

WND-CHARM is a multi-purpose image classifier that can be applied to a wide variety of image classification tasks without modifications or fine-tuning, and yet provides classification accuracy comparable to state-of-the-art task-specific image classifiers. WND-CHARM can extract up to ~3,000 generic image descriptors (features) including polynomial decompositions, high contrast features, pixel statistics, and textures. These features are derived from the raw image, transforms of the image, and compound transforms of the image (transforms of transforms). The features are filtered and weighted depending on their effectiveness in discriminating between a set of predefined image classes (the training set). These features are then used to classify test images based on their similarity to the training classes. This classifier was tested on a wide variety of imaging problems including biological and medical image classification using several imaging modalities, face recognition, and other pattern recognition tasks. WND-CHARM is an acronym that stands for "Weighted Neighbor Distance using Compound Hierarchy of Algorithms Representing Morphology."