Detect individual organelles in the 3D image stack including.
Detect individual nuclei in each of the 96 images and report.
Perform internal surface roughness measurement of a 3D dataset generated by a Versa X-ray microscopy (similar to computed tomography technique).
In order to obtain 3D printed parts with desired properties and biocompatibility, it is important to have a method to measure surface roughness on the interior of the part.
Analyze grains in a 3D dataset generated by scanning a rock sample on a Versa X-ray microscope (similar to computed tomography technique).
A grain can be multi-phase, so a single grain can have multiple densities (grey levels). And the fact that a high density member of the grain is exposed to the outside of the grain vs. being fully embedded is important.
Perform analysis of fibers on Scanning Electron Microscope (SEM) images.
Advanced materials such as insulators, absorbent material, filters, etc. have unique properties due to their fibrous structure. These properties depend on the characteristics of each individual fiber, such as size or distribution. In order to improve the design of these materials, an analysis of fibers is essential. However, segmentation of fibers is very challenging at the moment. An automated workflow would allow the researcher to perform a quick analysis instead of a very laborious manual measurement.
Segment round ‘blobs’ in down-sampled images obtained on the world’s fastest scanning electron microscope (MultiSEM).
Segment the blobs (shows on the next page) as separate individual blobs and report spatial distribution parameters such as density of blobs, size distribution, and position of each blob.
Detect individual mitochondria in the 3D image stack and report 3D morphological parameters such as volume, shape, surface area, etc.