Al-Hayek Y, Spuur K, Davidson R, Hayre C, Zheng X. The impacts of vertical off-centring, tube voltage, and Phantom size on computed tomography numbers: an experimental study. Radiography. 2022;28:641–7. https://doi.org/10.1016/j.jmir.2022.09.027.

Article  Google Scholar 

Dane B, O’Donnell T, Liu S, et al. Radiation dose reduction, improved isocenter accuracy and CT scan time savings with automatic patient positioning by a 3D camera. Eur J Radiol. 2021;136: 109537. https://doi.org/10.1016/j.ejrad.2021.109537.

Article  Google Scholar 

Yang K, Ruan C, Li X, Liu B. Data of CT bow tie filter profiles from three modern CT scanners. Data Brief. 2019;25: 104261. https://doi.org/10.1016/j.dib.2019.104261.

Article  Google Scholar 

Zhang G, Marshall N, Jacobs R, Liu Q, Bosmans H. Bowtie filtration for dedicated cone beam CT of the head and neck: a simulation study. Br J Radiol. 2013;86(1028): 20130002. https://doi.org/10.1259/bjr.20130002.

Article  Google Scholar 

Zhang J, Raslau FD, Hill N, Escott EJ. The importance of patient positioning when using a bowtie filter in computed tomography imaging. Radiol Technol. 2016;87(6):680–5.

Google Scholar 

Funama Y, Taguchi K, Awai K, Sakabe D, Shimamura M, Yamashita Y. Image noise and radiation dose using an automatic tube current modulation technique at 64-detector computed tomography: effect of off-center patient position, bowtie filter type, and scan projection radiograph. J Comput Assist Tomogr. 2009;33(6):973–7. https://doi.org/10.1097/RCT.0b013e31819d6f6f.

Article  Google Scholar 

Akin-Akintayo OO, Alexander LF, Neill R, et al. Prevalence and severity of off-centering during diagnostic CT: observations from 57,621 CT scans of the chest, abdomen, and/or pelvis. Curr Probl Diagn Radiol. 2019;48(3):229–34. https://doi.org/10.1067/j.cpradiol.2018.02.007.

Article  Google Scholar 

Mäkelä T, Kortesniemi M, Kaasalainen T. The impact of vertical off-centering on image noise and breast dose in chest CT with organ-based tube current modulation: A Phantom study. Phys Med. 2022;100:153–63. https://doi.org/10.1016/j.ejmp.2022.06.014.

Article  Google Scholar 

Kaasalainen T, Mäkelä T, Kortesniemi M. The effect of vertical centering and scout direction on automatic tube voltage selection in chest CT: a preliminary phantom study on two different CT equipments. Eur J Radiol Open. 2018;6:24–32. https://doi.org/10.1016/j.ejro.2018.12.001.

Article  Google Scholar 

Toth T, Ge Z, Daly MP. The influence of patient centering on CT dose and image noise. Med Phys. 2007;34(7):3093–101. https://doi.org/10.1118/1.2748113.

Article  Google Scholar 

Kataria B, Sandborg M, Althén JN. Implications of patient centring on organ dose in computed tomography. Radiat Prot Dosimetry. 2016;169(1–4):130–5. https://doi.org/10.1093/rpd/ncv527.

Article  Google Scholar 

Anam C, Haryanto F, Widita R, Arif I, Dougherty G, McLean D. Volume computed tomography dose index (CTDIvol) and size-specific dose estimate (SSDE) for tube current modulation (TCM) in CT scanning. Int J Radiat Res. 2018;16(3):289–97. https://doi.org/10.18869/acadpub.ijrr.16.2.289.

Article  Google Scholar 

Saltybaeva N, Schmidt B, Wimmer A, Flohr T, Alkadhi H. Precise and automatic patient positioning in computed tomography: avatar modeling of the patient surface using a 3-dimensional camera. Invest Radiol. 2018;53(11):641–6. https://doi.org/10.1097/RLI.0000000000000482.

Article  Google Scholar 

Furukawa Y, Matsubara K, Tsutsumi Y. A comparison of automatic and manual compensation methods for the calculation of tube currents during off-centered patient positioning with a noise-based automatic exposure control system in computed tomography. Phys Eng Sci Med. 2021;44(3):823–32. https://doi.org/10.1007/s13246-021-01033-y.

Article  Google Scholar 

Eberhard M, Blüthgen C, Barth BK, Frauenfelder T, Saltybaeva N, Martini K. Vertical off-centering in reduced dose chest-CT: impact on effective dose and image noise values. Acad Radiol. 2020;27(4):508–17. https://doi.org/10.1016/j.acra.2019.07.004.

Article  Google Scholar 

Barreto I, Lamoureux R, Olguin C, et al. Impact of patient centering in CT on organ dose and the effect of using a positioning compensation system: evidence from OSLD measurements in postmortem subjects. J Appl Clin Med Phys. 2019;20(6):141–51. https://doi.org/10.1002/acm2.12594.

Article  Google Scholar 

Anam C, Amilia R, Naufal A, et al. Automated patient centering of computed tomography images and its implementation to evaluate clinical practices in three hospitals in Indonesia. Pol J Med Phys Eng. 2022;28(4):207–14. https://doi.org/10.2478/pjmpe-2022-0024.

Article  Google Scholar 

Booij R, van Straten M, Wimmer A, Budde RPJ. Automated patient positioning in CT using a 3D camera for body contour detection: accuracy in pediatric patients. Eur Radiol. 2021;31(1):131–8. https://doi.org/10.1007/s00330-020-07097-w.

Article  Google Scholar 

Aly A, Ebrahimian S, Kharita MH, et al. Effect of technologist and patient attributes on centering for body CT examinations: influence of cultural and ethnic factors. PLoS One. 2022;17(8): e0273227. https://doi.org/10.1371/journal.pone.0273227.

Article  Google Scholar 

Higuchi S, Nishii T, Hirota A, et al. Patient positioning during pediatric cardiothoracic computed tomography using a high-resilience pad system and pre-scan measurement of chest thickness. Sci Rep. 2022;12: 16618. https://doi.org/10.1038/s41598-022-21018-5.

Article  Google Scholar 

DeWeese L, Griglock T, Moody A, Mehlberg A, Winters C. The improvement of patient centering in computed tomography through a technologist-focused education initiative. J Digit Imaging. 2022;35(2):327–34. https://doi.org/10.1007/s10278-021-00580-w.

Article  Google Scholar 

McCollough CH, Bruesewitz MR, McNitt-Gray MF, et al. The phantom portion of the American college of radiology (ACR) computed tomography (CT) accreditation program: practical tips, artifact examples, and pitfalls to avoid. Med Phys. 2004;31:2423. https://doi.org/10.1118/1.1769632.

Article  Google Scholar 

Mansour Z, Mokhtar A, Sarhan A, Ahmed MT, El-Diasty T. Quality control of CT image using American college of radiology (ACR) phantom. Egypt J Radiol Nucl Med. 2016;47(4):1665–71. https://doi.org/10.1016/j.ejrnm.2016.08.016.

Article  Google Scholar 

Zaila A, Adili M, Bamajboor S. Pylinac: a toolkit for performing TG-142 QA related tasks on linear accelerator. Phys Med. 2016;32:292–3. https://doi.org/10.1016/j.ejmp.2016.07.122.

Article  Google Scholar 

2017 American College of Radiology CT Accreditation Program Testing Instruction Revised 1–6.

Anam C, Amilia R, Naufal A, Dougherty G. Algorithm development for automatic laser alignment assessment on an ACR CT phantom and its evaluation on sixteen CT scanners. Biomed Phys Eng Express. 2023;9(6): 067002. https://doi.org/10.1088/2057-1976/acff76.

Article  Google Scholar 

Triche BL, Nelson JT Jr., McGill NS, et al. Recognizing and minimizing artifacts at CT, MRI, US, and molecular imaging. Radiographics. 2019;39(4):1017–8. https://doi.org/10.1148/rg.2019180022.