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Anam, Choirul, Triadyaksa, Pandji, Naufal, Ariij, Arifin, Zaenal, Muhlisin, Zaenul, Setiawati, Evi, Budi, Wahyu Setia. (1401). Impact of ROI Size on the Accuracy of Noise Measurement in CT on Computational and ACR Phantoms. سامانه مدیریت نشریات علمی, 12(4), 359-368. doi: 10.31661/jbpe.v0i0.2202-1457
Choirul Anam; Pandji Triadyaksa; Ariij Naufal; Zaenal Arifin; Zaenul Muhlisin; Evi Setiawati; Wahyu Setia Budi. "Impact of ROI Size on the Accuracy of Noise Measurement in CT on Computational and ACR Phantoms". سامانه مدیریت نشریات علمی, 12, 4, 1401, 359-368. doi: 10.31661/jbpe.v0i0.2202-1457
Anam, Choirul, Triadyaksa, Pandji, Naufal, Ariij, Arifin, Zaenal, Muhlisin, Zaenul, Setiawati, Evi, Budi, Wahyu Setia. (1401). 'Impact of ROI Size on the Accuracy of Noise Measurement in CT on Computational and ACR Phantoms', سامانه مدیریت نشریات علمی, 12(4), pp. 359-368. doi: 10.31661/jbpe.v0i0.2202-1457
Anam, Choirul, Triadyaksa, Pandji, Naufal, Ariij, Arifin, Zaenal, Muhlisin, Zaenul, Setiawati, Evi, Budi, Wahyu Setia. Impact of ROI Size on the Accuracy of Noise Measurement in CT on Computational and ACR Phantoms. سامانه مدیریت نشریات علمی, 1401; 12(4): 359-368. doi: 10.31661/jbpe.v0i0.2202-1457

Impact of ROI Size on the Accuracy of Noise Measurement in CT on Computational and ACR Phantoms

Journal of Biomedical Physics and Engineering
مقاله 5، دوره 12، شماره 4، آبان 2022، صفحه 359-368    اصل مقاله (1.65 M)
نوع مقاله: Original Research
شناسه دیجیتال (DOI): 10.31661/jbpe.v0i0.2202-1457
نویسندگان
Choirul Anam* 1؛ Pandji Triadyaksa1؛ Ariij Naufal2؛ Zaenal Arifin2؛ Zaenul Muhlisin2؛ Evi Setiawati2؛ Wahyu Setia Budi1
1PhD, Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Jl. Prof. Soedarto SH, Tembalang, Semarang 50275, Central Java, Indonesia
2MSc, Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Jl. Prof. Soedarto SH, Tembalang, Semarang 50275, Central Java, Indonesia
چکیده
Background: The effect of region of interest (ROI) size variation on producing accurate noise levels is not yet studied. 
Objective: This study aimed to evaluate the influence of ROI sizes on the accuracy of noise measurement in computed tomography (CT) by using images of a computational and American College of Radiology (ACR) phantoms.
Material and Methods: In this experimental study, two phantoms were used, including computational and ACR phantoms. A computational phantom was developed by using Matlab R215a software (Mathworks Inc., Natick, MA Natick, MA) with a homogeneously +100 Hounsfield Unit (HU) value and an added-Gaussian noise with various levels of 5, 10, 25, 50, 75, and 100 HU. The ACR phantom was scanned with a Philips MX-16 slice CT scanner in different slice thicknesses of 1.5, 3, 5, and 7 mm to obtain noise variation. Noise measurement was conducted at the center of the phantom images and four locations close to the edge of the phantom images using different ROI sizes from 3×3 to 41×41 pixels, with an increased size of 2×2 pixels. 
Results: The use of a minimum ROI size of 21×21 pixels shows noise in the range of ±5% ground truth noise. The measured noise increases above the ±5% range if the used ROI is smaller than 21×21 pixels.  
Conclusion: A minimum acceptable ROI size is required to maintain the accuracy of noise measurement with a size of 21×21 pixels.
کلیدواژه‌ها
ACR Phantom؛ Computational Phantom؛ Diagnostic Imaging؛ Image Quality؛ Noise Measurement؛ Radiologic Phantoms؛ Tomography, X-Ray Computed؛ X-Rays
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مراجع
  1. Solomon JB, Li X, Samei E. Relating noise to image quality indicators in CT examinations with tube current modulation. AJR Am J Roentgenol. 2013;200(3):592-600. doi: 10.2214/AJR.12.8580. PubMed PMID: 23436849.
  2. Nowik P, Bujila R, Poludniowski G, Fransson A. Quality control of CT systems by automated monitoring of key performance indicators: a two-year study. J Appl Clin Med Phys. 2015;16(4):254-65. doi: 10.1120/jacmp.v16i4.5469. PubMed PMID: 26219012. PubMed PMCID: PMC5690007.
  3. Schuhbaeck A, Schaefer M, Marwan M, Gauss S, et al. Patient-specific predictors of image noise in coronary CT angiography. J Cardiovasc Comput Tomogr. 2013;7(1):39-45. doi: 10.1016/j.jcct.2012.10.011. PubMed PMID: 23352772.
  4. Melnyk R, DiBianca FA. Modeling and measurement of the detector presampling MTF of a variable resolution x-ray CT scanner. Med Phys. 2007;34(3):1062-75. doi: 10.1118/1.2436977. PubMed PMID: 17369872. PubMed PMCID: PMC1828124.
  5. Anam C, Fujibuchi T, Budi WS, Haryanto F, Dougherty G. An algorithm for automated modulation transfer function measurement using an edge of a PMMA phantom: Impact of field of view on spatial resolution of CT images. J Appl Clin Med Phys. 2018;19(6):244-52. doi: 10.1002/acm2.12476. PubMed PMID: 30338920. PubMed PMCID: PMC6236841.
  6. Anam C, Fujibuchi T, Haryanto F, Budi WS, Sutanto H, et al. Automated MTF measurement in CT images with a simple wire phantom. Polish Journal of Medical Physics and Engineering. 2019;25(3):179-87. doi: 10.2478/pjmpe-2019-0024.
  7. Bellesi L, Wyttenbach R, Gaudino D, Colleoni P, et al. A simple method for low-contrast detectability, image quality and dose optimisation with CT iterative reconstruction algorithms and model observers. Eur Radiol Exp. 2017;1(1):18. doi: 10.1186/s41747-017-0023-4. PubMed PMID: 29708194. PubMed PMCID: PMC5909349.
  8. Anam C, Haryanto F, Widita R, Arif I. New noise reduction method for reducing CT scan dose: combining Wiener filtering and edge detection algorithm. AIP Conf Proc. 2015;1677(1):040004. doi: 10.1063/1.4930648.
  9. Zhou Y, Scott A, Allahverdian J, Lee C, et al. On the relationship of minimum detectable contrast to dose and lesion size in abdominal CT. Phys Med Biol. 2015;60(19):7671-94. doi: 10.1088/0031-9155/60/19/7671. PubMed PMID: 26389637.
  10. Viry A, Aberle C, Racine D, Knebel JF, Schindera ST, et al. Effects of various generations of iterative CT reconstruction algorithms on low-contrast detectability as a function of the effective abdominal diameter: A quantitative task-based phantom study. Phys Med. 2018;48:111-8. doi: 10.1016/j.ejmp.2018.04.006. PubMed PMID: 29728223.
  11. González-López A. Effect of noise on MTF calculations using different phantoms. Med Phys. 2018;45(5):1889-98. doi: 10.1002/mp.12847. PubMed PMID: 29500817.
  12. Mori I, Machida Y. Deriving the modulation transfer function of CT from extremely noisy edge profiles. Radiol Phys Technol. 2009;2(1):22-32. doi: 10.1007/s12194-008-0039-9. PubMed PMID: 20821125.
  13. Hsieh J. Computed Tomography: Principles, Design, Artifacts, and Recent Advances. SPIE Press; 2009. Chapter 5.
  14. Verdun FR, Racine D, Ott JG, Tapiovaara MJ, Toroi P, Bochud FO, Veldkamp WJH, Schegerer A, Bouwman RW, Giron IH, Marshall NW, Edyvean S. Image quality in CT: From physical measurements to model observers. Phys Med. 2015;31(8):823-43. doi: 10.1016/j.ejmp.2015.08.007. PubMed PMID: 26459319.
  15. Wu P, Stayman JW, Sisniega A, Zbijewski W, et al. Statistical weights for model-based reconstruction in cone-beam CT with electronic noise and dual-gain detector readout. Phys Med Biol. 2018;63(24):245018. doi: 10.1088/1361-6560/aaf0b4. PubMed PMID: 30524041.
  16. Brady SL, Yee BS, Kaufman RA. Characterization of adaptive statistical iterative reconstruction algorithm for dose reduction in CT: A pediatric oncology perspective. Med Phys. 2012;39(9):5520-31. doi: 10.1118/1.4745563. PubMed PMID: 22957619.
  17. Kim M, Lee JM, Yoon JH, Son H, et al. Adaptive iterative dose reduction algorithm in CT: effect on image quality compared with filtered back projection in body phantoms of different sizes. Korean J Radiol. 2014;15(2):195-204. doi: 10.3348/kjr.2014.15.2.195. PubMed PMID: 24644409. PubMed PMCID: PMC3955785.
  18. Anam C, Haryanto F, Widita R, Arif I, Dougherty G. An investigation of spatial resolution and noise in reconstructed CT images using iterative reconstruction (IR) and filtered back-projection (FBP). J Phys: Conf Series. 2019;1127(1):012016. doi: 10.1088/1742-6596/1127/1/012016.
  19. Rolstadaas L, Wasbø E. Variations in MTF and NPS between CT scanners with two different IR algorithms and detectors. Biomed Phys Eng Express. 2018;4(2):025009. doi: 10.1088/2057-1976/aa99ea.
  20. McCann C, Alasti H. Comparative evaluation of image quality from three CT simulation scanners. J Appl Clin Med Phys. 2004;5(4):55-70. doi: 10.1120/jacmp.v5i4.1978. PubMed PMID: 15738921. PubMed PMCID: PMC5723516.
  21. Anam C, Budi WS, Adi K, Sutanto H, et al. Assessment of patient dose and noise level of clinical CT images: automated measurements. J Radiol Prot. 2019;39(3):783-93. doi: 10.1088/1361-6498/ab23cc. PubMed PMID: 31117064.
  22. Brunner CC, Stern SH, Minniti R, Parry MI, Skopec M, Chakrabarti K. CT head-scan dosimetry in an anthropomorphic phantom and associated measurement of ACR accreditation-phantom imaging metrics under clinically representative scan conditions. Med Phys. 2013;40(8):081917. doi: 10.1118/1.4815964. PubMed PMID: 23927331.
  23. Husby E, Svendsen ED, Andersen HK, Martinsen ACT. 100 days with scans of the same Catphan phantom on the same CT scanner. J Appl Clin Med Phys. 2017;18(6):224-31. doi: 10.1002/acm2.12186. PubMed PMID: 28921910. PubMed PMCID: PMC5689914.
  24. Christe A, Heverhagen J, Ozdoba C, Weisstanner C, Ulzheimer S, Ebner L. CT dose and image quality in the last three scanner generations. World J Radiol. 2013;5(11):421-9. doi: 10.4329/wjr.v5.i11.421. PubMed PMID: 24349646. PubMed PMCID: PMC3856334.
  25. Kijewski MF, Judy PF. The noise power spectrum of CT images. Phys Med Biol. 1987;32(5):565-75. doi: 10.1088/0031-9155/32/5/003. PubMed PMID: 3588670.
  26. Nakahara S, Tachibana M, Watanabe Y. One-year analysis of Elekta CBCT image quality using NPS and MTF. J Appl Clin Med Phys. 2016;17(3):211-22. doi: 10.1120/jacmp.v17i3.6047. PubMed PMID: 27167279. PubMed PMCID: PMC5690923.
  27. Dolly S, Chen HC, Anastasio M, Mutic S, Li H. Practical considerations for noise power spectra estimation for clinical CT scanners. J Appl Clin Med Phys. 2016;17(3):392-407. doi: 10.1120/jacmp.v17i3.5841. PubMed PMID: 27167257. PubMed PMCID: PMC5690921.
  28. Specification and acceptance testing of computed tomography scanners. AAPM REPORT NO. 39; New York: AAPM; 1993.
  29. Samei E, Bakalyar D, Boedeker KL, Brady S, Fan J, et al. Performance evaluation of computed tomography systems: Summary of AAPM Task Group 233. Med Phys. 2019;46(11):e735-56. doi: 10.1002/mp.13763. PubMed PMID: 31408540.
  30. Dougherty G, Kawaf Z. The point spread function revisited: image restoration using 2-D deconvolution. Radiography. 2001;7(4):255-62. doi: 10.1053/radi.2001.0341.
  31. Gravel P, Beaudoin G, De Guise JA. A method for modeling noise in medical images. IEEE Trans Med Imaging. 2004;23(10):1221-32. doi: 10.1109/TMI.2004.832656. PubMed PMID: 15493690.
  32. Al-Kadi OS. Assessment of texture measures susceptibility to noise in conventional and contrast enhanced computed tomography lung tumour images. Comput Med Imaging Graph. 2010;34(6):494-503. doi: 10.1016/j.compmedimag.2009.12.011. PubMed PMID: 20060263.
  33. Mello-Amoedo CD, Martins AN, Tachibana A, Pinho DF, Baroni RH. Comparison of Radiation Dose and Image Quality of Abdominopelvic CT Using Iterative (AIDR 3D) and Conventional Reconstructions. AJR Am J Roentgenol. 2018;210(1):127-33. doi: 10.2214/AJR.17.18025. PubMed PMID: 29140117.
  34. Bujila R, Fransson A, Poludniowski G. Practical approaches to approximating MTF and NPS in CT with an example application to task-based observer studies. Phys Med. 2017;33:16-25. doi: 10.1016/j.ejmp.2016.10.016. PubMed PMID: 28003136.
  35. Assi AA, Arra AA. Optimization of image quality in pulmonary CT angiography with low dose of contrast material. Polish Journal of Medical Physics and Engineering. 2017;23(2):43-6. doi: 10.1515/pjmpe-2017-0008.
  36. Hussain FA, Mail N, Shamy AM, Suliman A, Saoudi A. A qualitative and quantitative analysis of radiation dose and image quality of computed tomography images using adaptive statistical iterative reconstruction. J Appl Clin Med Phys. 2016;17(3):419-32. doi: 10.1120/jacmp.v17i3.5903. PubMed PMID: 27167261. PubMed PMCID: PMC5690909.
  37. Hilts M, Jirasek A. Adaptive mean filtering for noise reduction in CT polymer gel dosimetry. Med Phys. 2008;35(1):344-55. doi: 10.1118/1.2818742. PubMed PMID: 18293589.
  38. Al-Hinnawi AR, Daear M, Huwaijah S. Assessment of bilateral filter on 1/2-dose chest-pelvis CT views. Radiol Phys Technol. 2013;6(2):385-98. doi: 10.1007/s12194-013-0212-7. PubMed PMID: 23605697.
  39. Li Z, Yu L, Trzasko JD, Lake DS, Blezek DJ, et al. Adaptive nonlocal means filtering based on local noise level for CT denoising. Med Phys. 2014;41(1):011908. doi: 10.1118/1.4851635. PubMed PMID: 24387516.
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