Terahertz time-of-flight tomography algorithm for different curvature samples.

Area of Science:

• Applied Physics
• Imaging Science

Background:

• Traditional terahertz reflection tomography is limited to planar or simple curvature samples.
• Complex shapes pose challenges for internal corrections and stitching in conventional imaging methods.

Purpose of the Study:

• To adapt terahertz time-of-flight tomography for imaging samples with abnormal curvature.
• To resolve challenges in point cloud position correction and improve reconstruction accuracy for complex geometries.

Main Methods:

• Utilized terahertz time-of-flight tomography with a rotating scanning array.
• Implemented a "point cloud splicing" method for comprehensive data collection.
• Developed a radial distance point cloud down-sampling technique to mitigate overlapping data effects.
• Applied Poisson surface reconstruction for enhanced visualization and accuracy.

Main Results:

• Achieved outer layer reconstruction error reduction to 0.22% after down-sampling.
• Attained a reconstruction accuracy of 0.01 mm using Poisson surface reconstruction.
• Successfully imaged samples with abnormal curvature, overcoming previous limitations.

Conclusions:

• Terahertz time-of-flight tomography with proposed methods is effective for complex shapes.
• This approach expands the applicability of terahertz reflection tomography.
• Offers a novel solution for non-destructive imaging of irregularly shaped objects.