When imaging is used in a material characterization project, scientists frown at its qualitative nature and limited sample size. Added complexity in sample prep and imaging expertise further intimidates scientists – what good can the time and resource expenditures truly bring us if the outcome is only some pretty pictures to look at?
We’ve been there, and totally agree. We believe that microstructure imaging entails the entire lifespan of an image, from its collection to its analysis, and even image-based simulation.
Imaging; Experimental design, representativeness, sample preparation
Analysis; Proprietary machine learning and deep learning technologies
Computing and Simulation; Cloud computing infrastructure and data management
We work with our clients throughout the entire imaging workflow, and adapts to any preferred insertion point.
We help our clients to design imaging experiments to address specific research, development, or manufacturing questions. DigiM can collect correlative 3D imaging data, or work with the imaging data that the clients collected in-house or elsewhere. We then quantify these massive amounts of imaging data, consistently and efficiently, using our AI-based image analysis algorithms. DigiM correlates the quantified parameters with processing conditions, formulation designs, manufacturing conditions, via image-based simulations, microstructure models, and deep material physics insight. Our workflow complies with FDA 21 CFR Part 11 requirements including full audit trail and reproducibility.
The best part? If anything goes wrong, you only need to complain to DigiM, instead of dealing with several different labs and software vendors. We can guarantee that we will take that complaint very seriously as we take pride in our collaborations with our clients.