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Original Research

Study on Dual-Energy Signal and Noise of Double-Exposure X-Ray Imaging for High Conspicuity

원문정보

Boram Song, Changsoo Kim, Junwoo Kim

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초록

영어

Background: Dual-energy X-ray images (DEI) can distinguish or improve materials of interest in a two-dimensional radiographic image, by combining two images obtained from separate low and high energies. The concepts of DEI performance describing the performance of doubleexposure DEI systems in the Fourier domain been previously introduced, however, the performance of double-exposure DEI itself in terms of various parameters, has not been reported. Materials and Methods: To investigate the DEI performance, signal-difference-to-noise ratio, modulation transfer function, noise power spectrum, and noise equivalent quanta were used. Low- and high-energy were 60 and 130 kVp with 0.01–0.09 mGy, respectively. The energyseparation filter material and its thicknesses were tin (Sn) and 0.0–1.0 mm, respectively. Noisereduction (NR) filtering used the Gaussian-filter NR, median-filter NR, and anti-correlated NR. Results and Discussion: DEI performance was affected by Sn-filter thickness, weighting factor, and dose allocation. All NR filtering successfully reduced noise, when compared with the dual-energy (DE) images without any NR filtering. Conclusion: The results indicated the significance of investigating, and evaluating suitable DEI performance, for DE images in chest radiography applications. Additionally, all the NR filtering methods were effective at reducing noise in the resultant DE images.

목차

ABSTRACT
Introduction
Materials and Methods
1. Dual-Energy X-ray Imaging
2. Noise Reduction
3. Measurements and Assessments
Results and Discussion
Conclusion
Conflict of Interest
Acknowledgements
Author Contribution
References

저자정보

  • Boram Song Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Korea
  • Changsoo Kim Department of Radiological Science, College of Health Sciences, Catholic University of Pusan, Busan, Korea
  • Junwoo Kim Center for Advanced Medical Engineering Research, Pusan National University, Busan, Korea

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