Amira for Advanced Image Processing and Quantification

In cell research scientist are imaging cells in their natural environment to observe their behavior. This also requires imaging multiple cells at the same time. This has the advantage of getting a large sample size for statistical analysis, but also requires more sophisticated image processing techniques to separate the cells prior to analysis.

The XImagePAQ extension for Amira Software offers a large variety of image processing algorithms that enable researchers to customize cell separation workflows to match any type of image data, cell shapes and variety. This animation demonstrates a typical cell separation and quantification workflow in Amira software and showcases the superior quality results achievable.

Micro-CT image acquisition is one of the most popular imaging technique for any type of bone research. One of the first steps for any type of bone analysis is bone segmentation and separation into individual bones.

The XImagePAQ extension for Amira Software offers the tools to perform bone segmentation from the surrounding tissue. The segmented bones can then be separated with the advanced XImagePAQ extension's algorithms. The individual bones can then be measured using a customizable list of the many measures that XImagePAQ extension provides, e.g. size, shape, and orientation measurements.

Bones typically consists of two types of osseous tissue, e.g. cortical and trabecular bone, giving bones their stiff and flexible properties. After separating bones and classifying them into different types, bone researchers are often interested in the morphology of the trabecular bone structures.

For this purpose, the XImagePAQ extension for Amira Software supports a workflow that separates the trabecular bone from the cortical bone. Once the two osseous tissues have been segmented, a series of bone morphometry measurements can be applied to quantify the trabecular bone structure.

3D electron microscopy data of biological tissue if often comprised of a high information density with grayscale values in a similar range only separated by thin structures or different texture of these structures.

This animation demonstrates the ease with which XImagePAQ extension for Amira Software enables image processing workflows to segment these different structures in complex tissue using 3D texture information.

Applications in dentistry, evolutionary biology or paleontology often aim at separating teeth that are in close proximity. The resolution limit of the imaging system typically prevents tooth segmentation by traditional means and often requires manual tracing of the teeth outline.

The advanced separation algorithms in XImagePAQ extension for Amira Software allow tooth separation workflows that will minimize the image processing time and deliver accurate and reproducible results.

In image analysis, structures of interest often have similar grayscale values to other structures or even artifacts in the image. They can only be distinguished by size, shape or other measurable parameters.

The XImagePAQ extension for Amira Software allows the segmentation of these structures, separating them from each other, quantifying them with a customizable list of nearly 100 measures and filtering them into categories to only extract the structures of interest.