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Biasing of Metal-Semiconductor Junctions01:27

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Biasing metal-semiconductor junctions involves applying a voltage across the junction. Specifically, the metal is connected to a voltage source, while the semiconductor is grounded. This technique is essential for controlling the direction and magnitude of current flow in electronic devices, including diodes, transistors, and photovoltaic cells.
In Schottky junctions, where the semiconductor is n-type, applying a positive voltage to the metal relative to the semiconductor reduces its Fermi...
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Projection-domain metal artifact correction using a dual layer detector.

Linxi Shi1, N Robert Bennett1, Josh Star-Lack2

  • 1Department of Radiology, Stanford University, Stanford, CA USA 94305.

Proceedings of Spie--The International Society for Optical Engineering
|July 12, 2021
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Summary

This study introduces a new single-pass method using a dual-layer detector to reduce metal artifacts in cone-beam CT images. This approach effectively identifies and corrects metal, improving image quality, especially with truncated or moving metal objects.

Keywords:
Metal artifactcone-beam CTdual energydual layermaterial decompositionprojection domain

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Area of Science:

  • Medical Imaging
  • Cone-Beam CT Technology
  • Artifact Reduction

Background:

  • Metal artifacts pose a significant challenge in cone-beam CT (CBCT) imaging.
  • Existing two-pass metal artifact reduction methods struggle with off-center or moving metal objects and increase scan time.

Purpose of the Study:

  • To investigate a novel projection-based metal artifact detection and correction method.
  • To evaluate the efficacy of a dual-layer detector for improved metal artifact reduction in CBCT.

Main Methods:

  • Utilized a dual-layer detector to acquire dual-energy images with precise spatial and temporal registration.
  • Developed a single-pass, projection-domain algorithm for metal artifact detection and correction.
  • Evaluated the method using a phantom with metal wires (copper) and a steel needle, comparing dual-layer to single-layer scans.

Main Results:

  • The dual-layer detector facilitated enhanced identification of metal regions within projections.
  • Substantially reduced metal artifacts were observed in the reconstructed images compared to single-layer scans.
  • Demonstrated improved performance in handling metal outside the scan field-of-view and during motion.

Conclusions:

  • A single-pass, projection-domain metal artifact reduction method using a dual-layer detector is effective.
  • This method shows promise for robustness against metal truncation and motion artifacts in CBCT.
  • The dual-layer detector approach offers a more efficient and accurate solution for metal artifact challenges.