Bimodal Visualization of Industrial X-Ray and Neutron Computed Tomography Data

Area of Science:

• Materials Science
• Computer Science
• Engineering

Background:

• Advanced manufacturing yields complex objects with challenging material compositions.
• Single-modality characterization is often insufficient for these materials.
• X-ray and neutron computed tomography offer complementary data but pose visualization challenges.

Purpose of the Study:

• To develop a novel interactive bimodal visualization approach for co-registered X-ray and neutron computed tomography data.
• To enable intuitive exploration of complex industrial objects by domain experts.
• To simplify the adjustment and exploration of bimodal transfer functions.

Main Methods:

• Designed an interactive bimodal visualization system integrating X-ray and neutron computed tomography data.
• Employed automatic topological segmentation of bivariate histograms as a starting point.
• Developed a widget with brushing interactions for correcting segmented histogram results.
• Utilized a semiautomated approach for intuitive data exploration.

Main Results:

• The system facilitates the creation, exploration, and adjustment of bimodal visualizations.
• Domain experts can intuitively explore large bimodal datasets without advanced technical knowledge.
• The approach effectively handles synthetic, phantom, and real-world industrial objects.

Conclusions:

• The novel interactive bimodal visualization approach simplifies the analysis of complex industrial objects.
• The system empowers domain experts to intuitively interpret complementary X-ray and neutron tomography data.
• This method enhances the characterization capabilities for advanced manufactured components.