AI Image Analysis

DigiM team has extensive experience in image processing. We help our clients to solve the toughest image processing problems efficiently and reproducibly. Whenever needed, we push the boundary of the state-of-the-art software algorithms offering customizable tools to combat any analysis challenge.

Image segmentation transforms greyscale values from images to material phases. Without accurate segmentation, further quantitative analysis cannot be performed, thus making it a critical step in any image workflow. DigiM team uses an iterative AI approach to image segmentation allowing users to get constant feedback on the quality of their segmentations to ensure accurate segmentations can be performed reliably and reproducibly.

Quantifications can be conducted on segmented images, as well as greyscale images. Quantitative assessment includes:

• Geometric quantification of microstructures (pores, defects, inclusions, particles, fibers, layers) in terms of their volume fraction, size distribution, connectivity, orientation, surface area, and more...
• Simulation of mass transport properties, such as permeability, diffusivity, elasticity, electrical conductivity, and thermal conductivity of each material
• Evaluation and generative AI predictions of microstructures in correlation with product performance, engineering process, and manufacturing conditions
• Quality control of microstructure (representativeness, uniformity, and composition)

DigiM AI analytical workflows are in compliance FDA 21 CFR Part 11. The results are reproducible with full audit trail support. All intermediate results, including segmentation, can be reviewed by the user.