Conference:
CIA-CT on industrial applications of Computed Tomography

With the growing clinical shift toward uncemented orthopaedic implants, ensuring reliable lattice structures is critical for achieving stable biological fixation.
Our work applies high‑resolution dimensional CT to verify the geometric fidelity and porosity of additively manufactured Ti6AL4V and PEEK lattices, parameters essential for osseointegration. CT‑derived metrics are then correlated with bone in‑growth potential, providing insight into design features that enhance fixation. In parallel, the same structural characteristics are evaluated for their influence on bacterial attachment, helping to map infection risk.
Together, these findings highlight the value of CT‑based assessment in balancing osseointegration performance with reduced infection‑related implant failure.

As additive manufacturing (AM) moves toward industrial series production of parts in critical sectors, compliance with geometric and dimensional specifications, within defined tolerances, must be demonstrated. AM enables highly complex geometries with internal structures, making X-ray Computed Tomography (XCT) an essential metrological tool. Although XCT lacks traceability, the growing need for metrology in AM series production implies standardized methodologies, including simplified approaches to measurement uncertainty.
This talk addresses XCT performance in terms of image quality and dimensional measurement accuracy within standardization to achieve this goal.

X-Ray technology plays a significant role in Non-Destructive Testing (NDT) of industrial parts across various sectors.
As the demand for speed, efficiency, and defect detection increases alongside growing part complexity, Artificial Intelligence (AI) solutions are becoming increasingly important.
This work examines the capabilities of AI in defect detection. It explores  AI solutions utilizing deep learning through case studies from diverse industry segments, highlighting their effectiveness and potential for enhancing NDT processes.

X‑ray microCT is a powerful, non‑destructive technique for examining drill cores, as it reveals their internal structure in 3D without cutting or altering the samples. It enables geoscientists to identify fractures, lithological boundaries, porosity features, and inclusions with high spatial resolution. The resulting datasets also support quantitative analysis—such as density variations or volume fractions—thereby improving geological interpretation. This work explores the application of X‑ray microCT for efficient core logging and highlights key requirements for advancing future applications.

Computed Tomography is increasingly deployed in quality control spanning food processing, agriculture, and wood products. While full CT acquisition remains the gold standard for detailed volumetric analysis, many inline inspection scenarios demand higher throughput than conventional scanning permits. When products come from a known domain with well-characterized material properties, sparse-projection strategies offer a practical path toward fast, scalable inspection.
This talk surveys real-world CT applications across diverse product types, illustrating how domain knowledge can guide the transition from full to sparse acquisition. We also touch on deep learning–based image analysis using the MONAI framework.

Dual‑energy X‑ray imaging can address key limitations of sparse‑view CT by providing accurate estimates of known material types along each ray path. Even with few projections, dual‑energy measurements enable separation of materials—such as lean, fat, and bone in meat inspection—and yield reliable per‑ray material distributions. When these distributions are combined across multiple angles and integrated with constraints from complementary vision‑based measurements, it becomes possible to derive parameters such as layer thickness and other internal structure. This can be used for fast, robust inspection of multi‑material objects where full CT acquisition is impractical, including but not limited to industrial meat processing where time is limited.

This presentation introduces a hierarchical multiscale X-ray phase-contrast tomography setup developed at DTU and implemented at the DanMAX beamline at MAX IV. The instrument enables imaging of centimeter-scale samples while resolving sub-micron and nanoscale structural details within the same optical configuration. Operating across the full DanMAX energy range (15–35 keV), the system combines a large field-of-view detector with multilayer Laue lenses to bridge the traditional trade-off between resolution and sample size. The approach enables acquisition of multiscale structural information from intact samples, providing both global context and fine internal features. The concept is compatible with higher-energy hard X-rays, making it suitable for dense materials such as minerals, rocks, and structural materials, while maintaining phase-contrast sensitivity for weakly absorbing biological specimens.

To be announced.