X-ray Micro-CT Analysis Services
High-resolution Insights for Your R&D
DigiM provides solutions across the whole suite of micro-CT and X-ray microscopy analysis, from imaging collection to image segmentation and modeling. We pride ourselves on designing the best imaging protocol and conditions across industries and samples, using computed tomography to study features at multiple scales. We work closely with our clients, using quantitative AI analysis to solve biggest R&D challenges. DigiM provides imaging and analysis with laboratory micro-CT , X-ray microscopy, and synchrotron based systems.
With X-ray microscopy, non-invasive 3D volumes can be collected at resolutions as high as half a micron.
Compared to traditional X-ray micro-CT systems, X-ray microscopy instruments utilize an optical lens and scintillator to magnify the signal received from the sample. This allows for local tomography, where a small region of interest within a sample can be selectively scanned at resolutions as high as half a micron.
The scan on the right demonstrates the use of X-ray microscopy to visualize thousands of particles in a spray dried powder, which is used in the pharmaceutical industry to manufacture tablets. XRM allows visualization of internal void space, as well as wall thickness, information otherwise hidden at low resolutions and with 2D imaging modalities.
Our frequently used instruments include:
- Zeiss Versa 520, Versa 610, and Versa 620 X-ray Microscope
- Zeiss Xradia Ultra 810 X-ray Microscope
- Rigaku nano3DX X-ray Microscope
- Rigaku CT Lab HX
- Rigaku CT Lab GX
- Bruker Skyscan 1272, 1273, and 1275 X-ray micro-CT
Deep learning analysis to classify and quantify particles, particles walls, voids, and inter-particle air space. A variety of critical quality attributes can be computed after phase classification.
At DigiM, we don’t stop at imaging – we believe all images have meaningful quantitative information which should be extracted. To analyze these complex microstructure images, we apply a suite of machine learning and deep learning analysis tools.
Common measurements include:
- Porosity and cracks
- Particle size distribution
- Spatial distribution
- Dimensional analysis
- Particle morphology and roundness
- Internal and external surface area
- Coating thickness
- Wall thickness