Automated assessment of low contrast sensitivity for CT systems using a model observer

Medical Physics

Volumn 38, Issue SUPPL.1, 2011, Pages

  Hernandez Giron, I ^a,b   Geleijns, J ^c   Calzado, A ^b   Veldkamp, W J H ^c  

^a FACULTAT DE MEDICINA I CIÈNCIES DE LA SALUT   (Spain)

^b UNIVERSIDAD COMPLUTENSE DE MADRID   (Spain)

^c LEIDEN UNIVERSITY MEDICAL CENTER   (Netherlands)

Author keywords

CT; dose; image quality; low contrast

Indexed keywords

AUTOMATION; IMAGE QUALITY; IMAGE RECONSTRUCTION; MATCHED FILTERS; PETROLEUM RESERVOIR EVALUATION; PHANTOMS;

ALTERNATIVE FORCED CHOICE; AUTOMATED ASSESSMENT; AUTOMATED MODELING; DOSE; IMAGE RECONSTRUCTION ALGORITHM; LOW CONTRAST; RECONSTRUCTION FILTERS; RECONSTRUCTION PARAMETERS;

COMPUTERIZED TOMOGRAPHY;

EID: 79960899037     PISSN: 00942405     EISSN: None     Source Type: Journal    
DOI: 10.1118/1.3577757     Document Type: Conference Paper

References (31)

1. D. J. Brenner, E. J. Hall, Computed tomography-An increasing source of radiation exposure., N. Engl. J. Med. 357, 2277-2284 (2007). 10.1056/NEJMra072149 (Pubitemid 350190758)
2. A. Berrington de Gonzlez, M. Mahesh, K. P. Kim, M. Bhargavan, R. Lewis, F. Mettler, and C. Land, Projected cancer risks from computed tomography scans performed in the United States in 2007., Arch. Intern. Med. 169, 2071-2077 (2009). 10.1001/archinternmed.2009.440
3. R. Smith-Bindman, Is computed tomography safe?, N. Engl. J. Med. 363, 1-4 (2010). 10.1056/NEJMp1002530
4. R. F. Redberg, Cancer risks and radiation exposure from computed tomographic scans: How can we be sure that the benefits outweight the risks?, Arch. Intern. Med. 169, 2049-2050 (2009). 10.1001/archinternmed.2009.453
5. A. C. T. Martinsen, H. K. Saether, D. R. Olsen, P. A. Wolff, and P. Skaane, Improved image quality of low-dose thoracic CT examinations with a new postprocessing software., J. Appl. Clin. Med. Phys. 11, 250-258 (2010), Available from: http://www.jacmp.org/index.php/jacmp/article/viewArticle/3242/ 1948.
6. International Commission on Radiation Units and Measurements, Receiver operating characteristic analysis in medical imaging., ICRU Report No. 79 (International Commission on Radiation Units and Measurements, Bethesda, MD, 2008).
7. M. S. Chesters, Human visual perception and ROC methodology in medical imaging., Phys. Med. Biol. 37, 1433-1476 (1992). 10.1088/0031-9155/37/7/001
8. A. Thilander-Klang, K. Ledenius, J. Hansson, P. Sund, and M. Bath, Evaluation of subjective assessment of the low-contrast visibility in constancy control of computed tomography., Radiat. Prot. Dosimetry 139, 449-454 (2010). 10.1093/rpd/ncq069
9. International Commission on Radiation Units and Measurements, Medical imaging-The assessment of image quality., ICRU Report No. 54 (International Commission on Radiation Units and Measurements, Bethesda, MD, 1996).
10. M. P. Eckstein, C. K. Abbey, and F. O. Bochud, A practical guide to model observers for visual detection in synthetic and natural noisy images., in Handbook of Medical Imaging. Physics and Psychophysics, Vol. 1, edited by, J. Beutel, H. L. Kundel, and, R. L. Van Metter, (SPIE, 2000), pp. 595-629.
11. E. H. Chao, T. L. Toth, N. B. Bromberg, E. C. Williams, S. H. Fox, and D. A. Carleton, A statistical method of defining low contrast detectability., Radiology 217, 162 (2000).
12. F. R. Verdun, A. Denys, P. S. Valley, R. A. Meuli, Detection of low-contrast objects: Experimental comparison of single-and multi-detector row CT., Radiology 223, 426-431 (2002). 10.1148/radiol.2232010810 (Pubitemid 34454321)
13. T. Ishida, S. Tsukagoshi, K. Kondo, K. Kainuma, M. Okumura, and T. Sasaki, Evaluation of dose efficiency index compared to receiver operating characteristics for assessing CT low-contrast performance., Proc. SPIE. 5368, 527-533 (2004). 10.1117/12.534519
14. S. J. Riederer, N. J. Pelc, and D. A. Chesler, The noise power spectrum in computed x-ray tomography., Phys. Med. Biol. 23, 446-454 (1978). 10.1088/0031-9155/23/3/008 (Pubitemid 8325901)
15. R. Brooks and G. Di Chiro, Statistical limitations in X-ray reconstructive tomography., Med. Phys. 3, 237-240 (1976). 10.1118/1.594240
16. Imaging Performance and Assessment of CT scanners, 32 to 64 slice CT scanner comparison report version 14., ImPACT Report 06013 (NHS Purchasing and supply agency, NHS PASA, 2005).
17. E. Burgess, F. L. Jacobson, and P. F. Judy, Human observer detection experiments with mammograms and power-law noise., Med. Phys. 28, 419-437 (2001). 10.1118/1.1355308 (Pubitemid 32323293)
18. I. Reiser and R. M. Nishikawa, Identification of simulated microcalcifications in white noise and mammographic backgrounds., Med. Phys. 33, 2905-2911 (2006). 10.1118/1.2210566 (Pubitemid 44154562)
19. B. M. Verbist, R. M. S. Joemai, W. M. Teeuwisse, W. J. H. Veldkamp, J. Geleijns, and J. H. M. Frijns, Evaluation of 4 multisection CT systems in postoperative imaging of a cochlear implant: A human cadaver and phantom study., AJNR 29, 1382-1388 (2008). 10.3174/ajnr.A1108
20. A. Wunderlich and F. Noo, Estimation of channelized hotelling observer performance with known class means or known difference of class means., IEEE Trans. Med. Imag. 28, 1198-1207 (2009). 10.1109/TMI.2009.2012705
21. W. J. H. Veldkamp, L. J. M. Kroft, J. P. Van Delft, and J. Geleijns, A technique for simulating the effect of dose reduction on image quality in digital chest radiography., J. Digit. Imag. 2, 1114-1125 (2009). 10.1007/s10278-008-9104-5
22. N. Karssemeijer and M. A. O. Thijssen, Determination of contrast-detail curves of mammography systems by automated image analysis., in Digital Mammography, edited by, K. Doi, M. L. Giger, R. M. Nishikawa, and, R. A. Schmidt, (Elsevier, Amsterdam, 1996), pp. 155-160.
23. W. J. H. Veldkamp, M. A. O. Thijssen, and N. Karssemeijer, The value of scatter removal by a grid in full field digital mammography., Med. Phys. 30, 1712-1718 (2003). 10.1118/1.1584044 (Pubitemid 36885788)
24. International Electrotechnical Commission, Medical electrical equipment. Part 2-44: Particular requirements for the safety of x-ray equipment for computed tomography, IEC publication No. 60601-2-44 (IEC, Geneva, Switzerland, 2002).
25. R. Fahrig, R. Dixon, T. Payne, and R. L. Morin, Dose and image quality for a cone-beam C-arm CT system., Med. Phys. 33, 4541-4550 (2006). 10.1118/1.2370508 (Pubitemid 44868090)
26. A. Ganguly, S. Yoon, and R. Fahrig, Dose and detectability for a cone-beam C-arm system revisited., Med. Phys. 37, 2264-2268 (2010). 10.1118/1.3397465
27. E. Samei, A. Badano, D. Chakraborty, K. Compton, C. Cornelius, K. Corrigan, M.J. Flynn, B. Hemminger, N. Hangiandreou, J. Johnson, D. M. Moxley-Stevens, W. Pavlicek, H. Roehrig, L. Rutz, J. Shepard, R. A. Uzenoff, J. Wang, and C. E. Willis, Assessment of display performance for medical imaging systems: Executive summary of AAPM TG18 report., Med. Phys. 32, 1205-1225 (2005). 10.1118/1.1861159 (Pubitemid 40586803)
28. R. F. Woolson, Statistical Methods of Analysis of Biomedical Data, 1st ed. (Wiley, New York, 1987), pp. 172-187.
29. L. M. Morn, R. Rodrguez, A. Calzado, A. Turrero, A. Arenas, A. Cuevas, B. García-Castao, N. Gmez, and P. Morn, Image quality and dose evaluation in spiral chest CT examinations of patients with lung carcinoma., Br. J. Radiol. 77, 839-846 (2004). 10.1259/bjr/71539623 (Pubitemid 39504639)
30. A. E. Burgess, Statistically defined backgrounds: Performance of a modified non-prewhitening observer model., J. Opt. Soc. Am. A 11, 1237-1242 (1994). 10.1364/JOSAA.11.001237
31. A. Wunderlich and F. Noo, Image covariance and lesion detectability in direct fan-beam x-ray computed tomography., Phys. Med. Biol. 53, 2471-2493 (2008). 10.1088/0031-9155/53/10/002 (Pubitemid 351595089)