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Related Concept Videos

Computed Tomography01:10

Computed Tomography

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Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
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Related Experiment Video

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Extracting Metrics for Three-dimensional Root Systems: Volume and Surface Analysis from In-soil X-ray Computed Tomography Data
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Assessment of Gradient-Based Algorithm for Surface Determination in Multi-Material Gap Measurements by X ray Computed

Roberto Jiménez-Pacheco1, Sinué Ontiveros2, José A Yagüe-Fabra3

  • 1Centro Universitario de la Defensa, A.G.M. Carretera Huesca s/n, 50090 Zaragoza, Spain.

Materials (Basel, Switzerland)
|December 16, 2020
PubMed
Summary

Gradient-based surface determination algorithms for X-ray computed tomography (CT) offer accurate measurements, especially in small gaps within multi-material industrial components. These advanced algorithms reduce user influence and computational costs compared to traditional methods.

Keywords:
computed tomographygap measurementsgradient-based algorithmmulti-material measurementssurface determination algorithm

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Area of Science:

  • Metrology and Industrial Imaging
  • Materials Science and Engineering

Background:

  • X-ray computed tomography (CT) is a key technique for dimensional evaluation of industrial parts.
  • Accurate surface determination in CT is challenging, particularly for multi-material components and small air gaps.
  • Existing threshold-based algorithms often struggle with complex geometries and introduce user variability.

Purpose of the Study:

  • To evaluate the performance of previously developed gradient-based surface determination algorithms.
  • To assess algorithm accuracy in complex multi-material scenarios, including metal-metal and polymer-metal interfaces with internal gaps.
  • To compare gradient-based methods against commercial threshold-based algorithms.

Main Methods:

  • Utilized a set of multi-material reference standards for testing.
  • Applied two gradient-based surface determination algorithms.
  • Compared measurement accuracy, gap measurement capability, and user influence against threshold-based methods.

Main Results:

  • Gradient-based algorithms demonstrated measurement errors comparable to commercial threshold-based algorithms.
  • The algorithms successfully provided accurate measurements in smaller internal gaps within multi-material parts.
  • Reduced user influence on the measurement process was observed with the gradient-based approaches.

Conclusions:

  • Gradient-based algorithms are effective for surface determination in complex multi-material CT applications.
  • These methods offer improved accuracy for small gap measurements and reduced operator dependency.
  • The findings support the adoption of gradient-based algorithms for enhanced dimensional evaluation in industrial CT.