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Classification of ring artifacts for their effective removal using type adaptive correction schemes.

Emran Mohammad Abu Anas1, Soo Yeol Lee, Kamrul Hasan

  • 1Department of Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology, Dhaka-1000, Bangladesh.

Computers in Biology and Medicine
|April 26, 2011
PubMed
Summary

This study introduces a new method to classify and remove ring artifacts in digital X-ray imaging. The technique effectively corrects both type I and type II artifacts, improving image quality.

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Area of Science:

  • Medical Imaging
  • Image Processing
  • Computational Science

Background:

  • High-resolution tomographic images from digital X-ray detectors frequently suffer from ring artifacts.
  • These artifacts degrade image quality, hindering accurate analysis and interpretation.

Purpose of the Study:

  • To classify, detect, and correct ring artifacts in digital X-ray tomographic images.
  • To develop separate, effective correction schemes for different types of ring artifacts.

Main Methods:

  • Proposed a novel classification of ring artifacts into type I (defective/dusty detector) and type II (mis-calibrated detector).
  • Utilized detector element response histograms and image inpainting for type I correction.
  • Employed Fast Fourier Transform (FFT) filtering and dc shift estimation for type II detection and correction.

Main Results:

  • The proposed method effectively distinguishes and corrects both type I and type II ring artifacts.
  • Evaluated using real micro-CT images, demonstrating superior performance compared to existing algorithms.
  • Simulation results confirm the effectiveness and superiority of the developed technique.

Conclusions:

  • The novel classification and separate correction strategies provide an effective solution for ring artifacts in tomographic imaging.
  • The proposed technique offers improved image quality for digital X-ray detector applications.
  • This method represents a significant advancement in artifact correction for high-resolution tomographic imaging.