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Computed Tomography01:10

Computed Tomography

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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In Vivo Quantification of Hip Arthrokinematics during Dynamic Weight-bearing Activities using Dual Fluoroscopy
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Data consistency based rigid motion artifact reduction in fan-beam CT.

Hengyong Yu1, Ge Wang

  • 1CT/Micro-CT Lab, Department of Radiology, University of Iowa, Iowa City, IA 52242, USA. hengyong-yu@ieee.org

IEEE Transactions on Medical Imaging
|February 20, 2007
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Summary

This study extends the Helgason-Ludwig consistency condition (HLCC) for rigid motion in fan-beam geometry. An iterative algorithm estimates motion parameters for improved medical image reconstruction.

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Area of Science:

  • Medical Imaging
  • Image Reconstruction
  • Computational Geometry

Background:

  • Rigid in-plane motion in imaging is typically decomposed into translation and rotation.
  • Accurate motion compensation is crucial for high-quality image reconstruction in medical imaging.
  • Existing methods may not fully address general rigid motion in fan-beam geometries.

Purpose of the Study:

  • To extend the Helgason-Ludwig consistency condition (HLCC) for general rigid motion in fan-beam geometry.
  • To develop an iterative algorithm for estimating in-plane motion parameters.
  • To enable motion-compensated image reconstruction.

Main Methods:

  • Extension of the Helgason-Ludwig consistency condition (HLCC) to fan-beam geometry.
  • Modeling of general rigid motion using parameterized variables.
  • Development of an iterative numerical optimization scheme to minimize an objective function based on the HLCC.
  • Image reconstruction using estimated motion parameters.

Main Results:

  • Successful extension of the HLCC for general rigid motion in fan-beam geometry.
  • Development and implementation of an iterative motion parameter estimation algorithm.
  • Demonstration of motion compensation effects through numerical simulations.

Conclusions:

  • The proposed iterative scheme effectively estimates motion parameters for rigid in-plane motion in fan-beam geometry.
  • The extended HLCC provides a robust foundation for motion compensation in image reconstruction.
  • The developed algorithm shows promise for improving the quality of reconstructed medical images affected by motion.