Computer analysis of mammography phantom images (CAMPI): An application to the measurement of microcalcification image quality of directly acquired digital images

Medical Physics

Volumn 24, Issue 8, 1997, Pages 1269-1277

  Chakraborty, Dev P ^a  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

ACR phantom; Computer analysis; Digital mammography

Indexed keywords

IMAGE ACQUISITION; IMAGE ANALYSIS; PHANTOMS; PHOTONS; QUALITY CONTROL; SIGNAL TO NOISE RATIO;

ACR PHANTOM; AMERICAN COLLEGE OF RADIOLOGIES; CLINICAL MAMMOGRAPHY; COMPUTER ANALYSIS; DIGITAL MAMMOGRAPHY; MICROCALCIFICATIONS; POISSON PHOTON STATISTICS; QUALITY CONTROL TOOL;

IMAGE QUALITY;

ARTICLE; CALCIFICATION; COMPUTER ANALYSIS; CONTRAST ENHANCEMENT; DIAGNOSTIC IMAGING; IMAGE QUALITY; MAMMOGRAPHY; PHANTOM; PRIORITY JOURNAL; RADIATION EXPOSURE;

EID: 0030743790     PISSN: 00942405     EISSN: None     Source Type: Journal    
DOI: 10.1118/1.598149     Document Type: Article

References (15)

1. D. P. Chakraborty and M. P. Eckert, "Quantitative versus subjective evaluation of mammography phantom images," Med. Phys. 22, 133-143 (1995).
2. D. P. Chakraborty, "Physical measures of image quality in mammography," SPIE Proceedings, Medical Imaging 1996, Physics of Medical Imaging, 2708, 179-193 (1996).
3. Federal Register, Part II, Department of Health and Human Services, Food and Drug Administration, 2ICFR Part 900. Mammography Quality Standards: Proposed Rules, April 3, 1996, Vol. 61, No. 65, pp. 14856-14920.
4. Actually a 31×31 pixel ROI was extracted for each speck. However, the shifting algorithm requires valid pixels on both sides of a point to generate the interpolated value. As this was not possible for the edge pixels, a 1 pixel edge region was dropped from each ROI, leaving a 29×29 pixel region for the analysis and plotting as in Figs. 1(a) and 1(b).
5. M. J. Tapiovaara and R. F. Wagner, "SNR and noise measurements for medical imaging: I. A practical approach based on statistical decision theory," Phys. Med. Biol. 38, 71-92 (1993).
6. M. J. Tapiovaara, "SNR and noise measurements for medical imaging: II. Application to fluoroscopic x-ray equipment,"Phys. Med. Biol. 38, 1761-1788 (1993).
7. D. P. Chakraborty and G. T. Barnes, "Signal-to-noise-ratio considerations in radiographic imaging," Med. Phys. 10, 467-469 (1983).
8. J. T. Bushberg, A. Seibert, E. M. Leidholdt, and J. M. Boone, The Essential Physics of Medical Imaging (Williams and Wilkins, Baltimore, MD, 1994).
9. T. S. Curry, J. E. Dowdey, and R. C. Murry, Christensen's Physics of Diagnostic Radiology, 4th ed. (Lea & Febiger, Philadelphia, PA, 1990).
10. R. Fahrig and M. J. Yaffe, "A model for optimization of spectral shape in digital mammography," Med. Phys. 21, 1463-1471 (1994).
11. D. P. Chakraborty, Q. Qian, and B. J. Yang, "Quantitative analysis of mammography phantom images: Extensions to methodology," Presented at 1995 AAPM Annual Meeting. Medical Physics as an electronic exhibit EP-E-01.D.
12. D. P. Chakraborty and B. J. Yang, "Image quality in mammography: Demonstration of a new quantitative phantom analysis method," RSNA '95 Scientific Program, 197 (P): 452, Exhibit 088PH (1995).
13. L. E. Antonuk, J. Yorkston, W. Huang, J. Boudry, E. J. Morton, and R. A. Street, "Large area, flat panel a-Si:H arrays for x-ray imaging," SPIE Proceedings, Medical Imaging 93, 1896, 18-29 (1993).
14. D. L. Lee, L. K. Cheung, and L. S. Jeromin, "A New Digital Detector for Projection Radiography," SPIE Proceedings, Physics of Medical Imaging, 2432, 237-249 (1995).
15. N. R. Draper and H. Smith, Applied Regression Analysis, 2nd ed. (Wiley, New York, 1981), Chap. 1.