AI Reconstruction Uses Deep Learning To Deliver Faster and Clearer CT Scans –
Summary
The Deep Learning modelling underpinning AI Reconstruction is trained to distinguish relevant information from the scan artifacts to effectively filter noise and improve clarity. This technology leap helps testing and quality teams enhance throughput and precision like never before — the dramatically sharper image quality reveals minute product flaws that used to require painstaking scans, while the faster scan speeds let users reliably analyse many more units per day.” Examples of where this technology will demonstrate a profound impact include the automotive, aerospace and manufacturing sectors, as well as the medical device industry. These guidelines propose seven key requirements for trustworthy AI systems: human agency and oversight, technical robustness and safety, privacy and data governance, transparency, diversity, non-discrimination and fairness, societal and environmental well-being, and accountability. By automatically analysing the 3D CT scan data using AI, LiB.Overhang Analysis can accurately measure the critical dimensions of anode overhang regions in LiB cells to ensure they are within the required tolerances for optimal battery performance and safety. That means many more sectors can benefit, creating unprecedented opportunities for improvement in areas including castings, additive manufacturing, as well as academia, research and many more.” Nikon’s AI Reconstruction is provided as a tailored service drawing on the company’s expertise in meeting specific customer needs.