UNDERSTANDING RADIOGRAPHIC IMAGE NOISE MEASUREMENT AND REMOVAL
Main Article Content
Abstract
Background: The radiographic image is characterized by image noise arising from random fluctuations in the absorption of photons by the imaging medium or detector. Measurement and removal of these perturbations will increase the quality of the signal which is desired in improving image interpretation.
Purpose: This paper is a short review to improve understanding of the phenomena.
Method: A review of some literature was undertaken to facilitate improved appreciation of noise and its measurement. Use of filters in the removal of image noise is covered the review.
Conclusion: An understanding of image noise and its contributing parameters is essential to the utilization of post processing techniques for improving image quality.
Downloads
Article Details
Section
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
All articles in JRRS are published under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
How to Cite
References
European Society of Radiology. (2010). The future role of radiology in healthcare. Insights into Imaging, 1(1), 2–11.
Li, X., Samei, E., Barnhart, H. X., Gaca, A. M., Hollingsworth, C. L., Maxfield, C. M., et al. (2011). Lung nodule detection in pediatric chest CT: Quantitative relationship between image quality and radiologist performance. Medical Physics, 38(5), 2609–2618.
Ekpo, E. U., & McEntee, M. F. (2016). An evaluation of performance characteristics of primary display devices. Journal of Digital Imaging, 29(2), 175–182.
Saunders, R. S., Jr., Baker, J. A., Delong, D. M., Johnson, J. P., & Samei, E. (2007). Does image quality matter? Impact of resolution and noise on mammographic task performance. Medical Physics, 34(10), 3971–3981.
Ekpo, E. U., Hoban, A. C., & McEntee, M. F. (2014). Optimisation of direct digital chest radiography using Cu filtration. Radiography, 20(4), 346–350.
Saunders, R. S., Jr., & Samei, E. (2003). A method for modifying the image quality parameters of digital radiographic images. Medical Physics, 30(11), 3006–3017.
Floyd, C. E., Jr., Warp, R. J., Dobbins, J. T., 3rd, Chotas, H. G., Baydush, A. H., Vargas-Voracek, R., et al. (2001). Imaging characteristics of an amorphous silicon flat-panel detector for digital chest radiography. Radiology, 218(3), 683–688.
Ekpo, E. U., Suleman, B., Elaine, R., Peter, H., & Mark, F. M. (2016). Operator eye doses during computed tomography fluoroscopic lung biopsy. Journal of Radiological Protection, 36(2), 290.
Seeram, E., & Seeram, D. (2014). Image postprocessing in digital radiology: A primer for technologists. Journal of Medical Imaging & Radiation Sciences, 39(1), 23–41.
Shinde, B. M. D., & Dani, A. R. (2012). Study of noise detection and noise removal techniques in medical images. I.J. Image, Graphics and Signal Processing, 2, 51–60.
Samei, E. (2003). Performance of digital radiographic detectors: Quantification and assessment methods. In Advances in Digital Radiography: RSNA Categorical Course in Diagnostic Radiology Physics (pp. 37–47).
Siewerdsen, J. H., Antonuk, L. E., el-Mohri, Y., Yorkston, J., Huang, W., & Cunningham, I. A. (1998). Signal, noise power spectrum, and detective quantum efficiency of indirect-detection flat-panel imagers for diagnostic radiology. Medical Physics, 25(5), 614–628.
Goldman, L. W. (2007). Principles of CT: Radiation dose and image quality. Journal of Nuclear Medicine Technology, 35(4), 213–225; quiz 226–228.
Chandler, D. M. (2013). Seven challenges in image quality assessment: Past, present, and future research. ISRN Signal Processing, 2013, Article ID 905685, 53.
Ziegler, A., Kohler, T., & Proksa, R. (2007). Noise and resolution in images reconstructed with FBP and OSC algorithms for CT. Medical Physics, 34(2), 585–598.
Zhu, Y., & Huang, C. (2012). An improved median filtering algorithm for image noise reduction. Physics Procedia, 25, 609–616.
Zeng, H., Liu, Y.-Z., Fan, Y.-M., & Tang, X. (2012). An improved algorithm for impulse noise by median filter. AASRI Procedia, 1, 68–73.