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Journal of the Optical Society of America A

Journal of the Optical Society of America A


  • Vol. 19, Iss. 7 — Jul. 1, 2002
  • pp: 1297–1307

Quantitative assessment of image quality enhancement due to unsharp-mask processing in x-ray fluoroscopy

Kadri N. Jabri and David L. Wilson  »View Author Affiliations

JOSA A, Vol. 19, Issue 7, pp. 1297-1307 (2002)

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Spatial unsharp-mask processing and its variants are commonly used in x-ray radiography to enhance image contrast. We investigated the effect of three unsharp-masking filter kernels of different sizes on the detection of an advanced guidewire tip in simulated x-ray fluoroscopy image sequences. To isolate the effect of visual temporal processing, we repeated the experiments on single images. Filter gains were selected so that all three kernels increased the contrast of a 0.018-in. (0.457-mm) guidewire by a factor of 2 but had different effects on image noise and signal profiles. There was no statistically significant effect of unsharp masking on human-observer performance in single images. However, all three kernels significantly improved average performance in image sequences, and the guidewire contrast required for detection was reduced by 32%–40%. A prewhitening channelized observer model predicted the disparity between sequences and single images and fitted measurements at different kernel sizes well. A nonprewhitening observer model did not. We conclude that unsharp masking is a simple and effective method of improving guidewire visualization in fluoroscopically guided interventional procedures and that quantitative image quality studies are essential for evaluation of image-processing techniques in sequences such as x-ray fluoroscopy.

© 2002 Optical Society of America

OCIS Codes
(100.2000) Image processing : Digital image processing
(100.2980) Image processing : Image enhancement
(330.1880) Vision, color, and visual optics : Detection
(330.5370) Vision, color, and visual optics : Physiological optics

Original Manuscript: August 14, 2001
Revised Manuscript: January 7, 2002
Manuscript Accepted: January 7, 2002
Published: July 1, 2002

Kadri N. Jabri and David L. Wilson, "Quantitative assessment of image quality enhancement due to unsharp-mask processing in x-ray fluoroscopy," J. Opt. Soc. Am. A 19, 1297-1307 (2002)

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  1. L. K. Wagner, M. D. McNeese, M. V. Marx, E. L. Siegel, “Severe skin reactions from interventional fluoroscopy: case report and review of the literature,” Radiology 213, 776 (1999). [CrossRef]
  2. J. C. Brailean, R. P. Kleihorst, S. N. Efstratiadis, A. K. Katsaggelos, R. L. Lagendijk, “Noise reduction filters for dynamic image sequences: a review,” Proc. IEEE 83, 1272–1292 (1995). [CrossRef]
  3. C. L. Chan, A. K. Katsaggelos, A. V. Sahakian, “Image sequences filtering in quantum-limited noise with applications to low-dose fluoroscopy,” IEEE Trans. Med. Imaging 12, 610–621 (1993). [CrossRef]
  4. C. L. Chan, A. K. Katsaggelos, A. V. Sahakian, “Linear-quadratic noise-smoothing filters for quantum-limited images,” IEEE Trans. Image Process. 4, 1328–1333 (1995). [CrossRef]
  5. D. L. Wilson, K. N. Jabri, R. Aufrichtig, “Perception of temporally filtered x-ray fluoroscopy images,” IEEE Trans. Med. Imaging 18, 22–31 (1999). [CrossRef] [PubMed]
  6. K. N. Jabri, D. L. Wilson, “Detection improvement in spatially filtered x-ray fluoroscopy image sequences,” J. Opt. Soc. Am. A 16, 742–749 (1999). [CrossRef]
  7. F. J. Sanchez-Marin, Y. Srinivas, K. N. Jabri, D. L. Wilson, “Quantitative image quality analysis of a non-linear spatio-temporal filter,” IEEE Trans. Image Process. 10, 288–295 (2001). [CrossRef]
  8. A. K. Jain, Fundamentals of Digital Image Processing (Prentice-Hall, Englewood Cliffs, N.J., 1989).
  9. A. P. Dhawan, G. Buelloni, R. Gordon, “Enhancement of mammographic features by optimal adaptive neighborhood image processing,” IEEE Trans. Med. Imaging MI-5, 8–15 (1986). [CrossRef]
  10. M. Prokop, C. M. Schaefer, J. W. Oestmann, M. Galanski, “Improved parameters for unsharp mask filtering of digital chest radiographs,” Radiology 187, 521–526 (1993). [PubMed]
  11. R. C. Gonzalez, R. E. Woods, Digital Image Processing (Addison-Wesley, Reading, Mass., 1992).
  12. M. Stahl, T. Aach, S. Dippel, “Digital radiography enhancement by nonlinear multiscale processing,” Med. Phys. 27, 56–65 (2000). [CrossRef] [PubMed]
  13. F. Li, S. Sone, K. Kiyono, “Lung nodule conspicuity using unsharp mask filters with storage-phosphor-based computed radiography,” Acta Radiol. 38, 99–103 (2000). [CrossRef]
  14. Z.-G. Yang, S. Sone, F. Li, S. Takashima, Y. Maruyama, M. Hasegawa, K. Hanamura, K. Asakura, “Detection of small peripheral lung cancer by digital chest radiography: Performance of unprocessed versus unsharp mask-processed images,” Acta Radiol. 40, 505–509 (1999). [CrossRef] [PubMed]
  15. R. D. Muller, M. Voss, H. Hirche, B. Buddenbrock, V. John, E. Bosch, “Unsharp masking of low-dosed digital luminescence radiographs: results of a receiver operating characteristics analysis,” Eur. Radiol. 6, 526–531 (1996). [CrossRef] [PubMed]
  16. W. Huda, C. J. Belden, L. A. Webb, C. K. Palmer, “Support line and tube visibility in chest examinations using computed radiography,” J. Digital Imag. 10, 126–131 (1997). [CrossRef]
  17. R.-D. Muller, D. Herting, H. Hirche, V. John, B. Buddenbrock, P. Gocke, R. Wiebringhaus, R. Braunschweig, M. Voss, M. Mohnke, N. Konietzko, “Effects of varying filter kernel sizes on the image quality of interstitial lung diseases,” Acta Radiol. 37, 732–740 (1996). [CrossRef] [PubMed]
  18. A. Katsumi, S. Katsuragawa, Y. Sasaki, T. Yanagisawa, “A fully automated adaptive unsharp masking technique in digital chest radiograph,” Invest. Radiol. 27, 64–70 (1991).
  19. P. Vuylsteke, E. Schoeters, “Multiscale image contrast amplification (MUSICA),” in Medical Imaging 1994: Image Processing, M. H. Loew, ed., Proc. SPIE2167, 551–560 (1994). [CrossRef]
  20. L. D. Loo, K. Doi, C. E. Metz, “Investigation of basic imaging properties in digital radiography. 4. Effect of unsharp masking on the detectability of simple patterns,” Med. Phys. 12, 209–214 (1985). [CrossRef] [PubMed]
  21. R. Aufrichtig, “Comparison of low contrast detectability between a digital amorphous silicon and a screen-film based imaging system for thoracic radiography,” Med. Phys. 26, 1349–1358 (1999). [CrossRef] [PubMed]
  22. K. J. Myers, H. H. Barrett, M. C. Borgstrom, D. D. Patton, G. W. Seeley, “Effect of noise correlation on detectability of disk signals in medical imaging,” J. Opt. Soc. Am. A 2, 1752–1759 (1985). [CrossRef] [PubMed]
  23. A. E. Burgess, “Visual signal detection with two-component noise: low-pass spectrum effects,” J. Opt. Soc. Am. A 16, 694–704 (1999). [CrossRef]
  24. M. Ishida, K. Doi, L.-N. Loo, C. E. Metz, J. L. Lehr, “Digital image processing: Effect on detectability of simulated low-contrast radiographic patterns,” Radiology 150, 569–575 (1984). [PubMed]
  25. A. E. Burgess, “Statistically defined backgrounds: performance of a modified nonprewhitening observer model,” J. Opt. Soc. Am. A 11, 1237–1242 (1994). [CrossRef]
  26. R. Aufrichtig, C. W. Thomas, P. Xue, D. L. Wilson, “Model for perception of pulsed fluoroscopy image sequences,” J. Opt. Soc. Am. A 11, 3167–3176 (1994). [CrossRef]
  27. P. Xue, D. L. Wilson, “Detection of moving objects in pulsed x-ray fluoroscopy,” J. Opt. Soc. Am. A 15, 375–388 (1998). [CrossRef]
  28. D. H. Kelly, “Motion and vision, II: stabilized spatiotemporal threshold surface,” J. Opt. Soc. Am. 69, 1340–1349 (1979). [CrossRef] [PubMed]
  29. A. E. Burgess, X. Li, C. K. Abbey, “Visual signal detectability with two noise components: anomalous masking effects,” J. Opt. Soc. Am. A 14, 2420–2442 (1997). [CrossRef]
  30. A. E. Burgess, B. Colborne, “Visual signal detection. IV. Observer inconsistency,” J. Opt. Soc. Am. A 5, 617–627 (1988). [CrossRef] [PubMed]
  31. K. J. Myers, H. H. Barrett, “Addition of a channel mechanism to the ideal-observer model,” J. Opt. Soc. Am. A 4, 2447–2457 (1987). [CrossRef] [PubMed]
  32. P. Xue, C. W. Thomas, G. C. Gilmore, D. L. Wilson, “An adaptive reference/test paradigm: application to pulsed fluoroscopy perception,” Behav. Res. Meth. Instrum. Comput. 30, 332–348 (1998). [CrossRef]
  33. P. Xue, D. L. Wilson, “Pulsed fluoroscopy detectability from interspersed adaptive forced-choice measurements,” Med. Phys. 23, 1833–1843 (1996). [CrossRef] [PubMed]
  34. P. R. Granfors, “Performance characteristics of an amorphous silicon flat panel x-ray imaging detector,” in Medical Imaging 1999: Physics of Medical Imaging, J. M. Boone, J. T. Dobbins, eds., Proc. SPIE3659, 480–490 (1999). [CrossRef]
  35. D. C. Montgomery, G. C. Runger, Applied Statistics and Probability for Engineers (Wiley, New York, 1999).
  36. J. S. Whiting, M. P. Eckstein, C. A. Morioka, N. L. Eigler, “Effect of additive noise, signal contrast, and feature motion on visual detection in structured noise,” in Medical Imaging 1996: Image Perception, H. L. Kundel, ed., Proc. SPIE2712, 26–38 (1996). [CrossRef]
  37. R. N. McDonough, A. D. Whalen, Detection of Signals in Noise, 2nd ed. (Academic Press, San Diego, Calif., 1995).
  38. R. E. Fredericksen, R. F. Hess, “Temporal detection in human vision: Dependence on spatial frequency,” J. Opt. Soc. Am. A 16, 2601–2611 (1999). [CrossRef]
  39. J. T. Dobbins, J. T. Rice, C. A. Beam, C. E. Ravin, “Threshold perception performance with computed and screen-film radiography: implications for chest radiography,” Radiology 183, 179–187 (1992). [PubMed]
  40. E. Samei, M. J. Flynn, W. R. Eyler, “Detection of subtle lung nodules: Relative influence of quantum and anatomic noise on chest radiographs,” Radiology 213, 734 (1999). [CrossRef]
  41. F. O. Bochud, J.-F. Valley, F. R. Verdun, “Estimation of the noisy component of anatomical backgrounds,” Med. Phys. 26, 1365–1370 (1999). [CrossRef] [PubMed]
  42. Y. Srinivas, K. N. Jabri, F. J. Sanchez-Marin, D. L. Wilson, “Quantitative image quality evaluation of temporal and spatio-temporal filtering of x-ray fluoroscopy sequences,” Med. Phys. 27, 1447 (2000).

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