Advertisement

Cone-Beam CT Systems

  • Jeffrey H. SiewerdsenEmail author
Chapter

Abstract

Cone-beam CT (CBCT) systems have emerged in a broad variety of forms and clinical applications. The diversity of platforms includes open-gantry C-arms and U-arms as well as closed-gantry rings. Applications span a spectrum of image-guided interventions (e.g., image-guided radiotherapy, surgery, and interventional radiology) and specialty diagnostic imaging procedures (e.g., dental, ENT, breast, and orthopedics). This chapter surveys the general principles and characteristics of CBCT in comparison and in contrast to multi-detector CT (MDCT). Aspects of particular note include system geometry, x-ray source and detector, 3D image acquisition and reconstruction techniques, image quality characteristics, artifacts, dosimetry, primary areas of clinical application, and regulatory considerations.

Keywords

Cone-beam CT Multi-detector CT Flat-panel detector Volumetric imaging 3D image reconstruction Artifact correction Image quality C-arm Image-guided interventions 

References

  1. 1.
    Hsieh J. Computed tomography: principles, design, artifacts, and recent advances. Computed tomography: principles, design, artifacts, and recent advances. 2nd ed. Bellingham: SPIE; 2015.CrossRefGoogle Scholar
  2. 2.
    Buzug TM. Computed tomography: from photon statistics to modern cone-beam CT. Berlin: Springer; 2008.Google Scholar
  3. 3.
    Shaw C, editor. Cone beam computed tomography imaging in medical diagnosis and therapy. Boca Raton: CRC; 2014.Google Scholar
  4. 4.
    Brock KK, editor. Image processing in radiation therapy imaging in medical diagnosis and therapy. Boca Raton: CRC; 2016.Google Scholar
  5. 5.
    Zhou SK, editor. Handbook of medical image computing and computer assisted intervention. Boca Raton: CRC; 2019.Google Scholar
  6. 6.
    Siewerdsen JH, Moseley DJ, Burch S, Bisland SK, Bogaards A, Wilson BC, et al. Volume CT with a flat-panel detector on a mobile, isocentric C-arm: pre-clinical investigation in guidance of minimally invasive surgery. Med Phys [Internet]. 2005 [cited 2014 May 27];32(1):241–254. Available from: http://www.ncbi.nlm.nih.gov/pubmed/15719975.PubMedCrossRefPubMedCentralGoogle Scholar
  7. 7.
    Jaffray DA, Siewerdsen JH, Wong JW, Martinez AA. Flat-panel cone-beam computed tomography for image-guided radiation therapy. Int J Radiat Oncol Biol Phys [Internet]. 2002 [cited 2014 May 27];53(5):1337–1349. Available from: http://www.ncbi.nlm.nih.gov/pubmed/12128137.CrossRefGoogle Scholar
  8. 8.
    Uneri A, Zhang X, Stayman JW, Helm P, Osgood GM, Theodore N, et al. Advanced image registration and reconstruction using the O-arm system: dose reduction, image quality, and guidance using known-component models. In: Webster RJ, Fei B, editors. SPIE medical imaging. Houston: SPIE; 2018. p. 43.Google Scholar
  9. 9.
    Siewerdsen JH. Cone-beam CT with a flat-panel detector: from image science to image-guided surgery. Nucl Instrum Methods Phys Res A [Internet]. 2011 [cited 2014 May 27];648(S1):S241–S250. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3429946&tool=pmcentrez&rendertype=abstract.
  10. 10.
    Fahrig R, Dixon R, Payne T, Morin RL, Ganguly A, Strobel N. Dose and image quality for a cone-beam C-arm CT system. Med Phys [Internet]. 2006;33(12):4541–50. Available from: http://www.ncbi.nlm.nih.gov/pubmed/17278805.CrossRefGoogle Scholar
  11. 11.
    Lauzier PT, Tang J, Chen G-H. Time-resolved cardiac interventional cone-beam CT reconstruction from fully truncated projections using the prior image constrained compressed sensing (PICCS) algorithm. Phys Med Biol [Internet]. 2012;57(9):2461–76. Available from: http://stacks.iop.org/0031-9155/57/i=9/a=2461?key=crossref.9bc9545e6024e4a480c719410b4ec593.PubMedPubMedCentralCrossRefGoogle Scholar
  12. 12.
    Pauwels R, Araki K, Siewerdsen JH, Thongvigitmanee SS. Technical aspects of dental CBCT: state of the art. Dentomaxillofacial Radiol [Internet]. 2015;44(1):20140224. Available from: http://www.birpublications.org/doi/10.1259/dmfr.20140224.CrossRefGoogle Scholar
  13. 13.
    Xu J, Reh DD, Carey JP, Mahesh M, Siewerdsen JH. Technical assessment of a cone-beam CT scanner for otolaryngology imaging: image quality, dose, and technique protocols. Med Phys [Internet]. 2012 [cited 2014 May 27];39(8):4932–4942. Available from: http://www.ncbi.nlm.nih.gov/pubmed/22894419.PubMedCrossRefGoogle Scholar
  14. 14.
    Boone JM, Kwan ALC, Yang K, Burkett GW, Lindfors KK, Nelson TR. Computed tomography for imaging the Breast. J Mammary Gland Biol Neoplasia [Internet]. 2006;11(2):103–11. Available from: http://link.springer.com/10.1007/s10911-006-9017-1.CrossRefGoogle Scholar
  15. 15.
    Carrino JA, Al Muhit A, Zbijewski W, Thawait GK, Stayman JW, Packard N, et al. Dedicated cone-beam CT system for extremity imaging. Radiology [Internet]. 2014 Mar [cited 2014 May 27];270(3):816–824. Available from: http://www.ncbi.nlm.nih.gov/pubmed/24475803.PubMedCrossRefPubMedCentralGoogle Scholar
  16. 16.
    Feldkamp LA, Davis LC, Kress JW. Practical cone-beam algorithm. J Opt Soc Am A [Internet]. 1984;1(6):612. Available from: https://www.osapublishing.org/abstract.cfm?URI=josaa-1-6-612.CrossRefGoogle Scholar
  17. 17.
    Uneri A, Zhang X, Yi T, Stayman JW, Helm PA, Theodore N, et al. Image quality and dose characteristics for an O-arm intraoperative imaging system with model-based image reconstruction. Med Phys [Internet]. 2018;45(11):4857–68. Available from: https://onlinelibrary.wiley.com/doi/abs/10.1002/mp.13167.CrossRefGoogle Scholar
  18. 18.
    Liang JZ, La Riviere PJ, El Fakhri G, Glick SJ, Siewerdsen J. Guest editorial low-dose CT: what has been done, and what challenges remain? IEEE Trans Med Imaging [Internet]. 2017;36(12):2409–16. Available from: http://ieeexplore.ieee.org/document/8125482/.CrossRefGoogle Scholar
  19. 19.
    Stayman JW, Dang H, Ding Y, Siewerdsen JH. PIRPLE: a penalized-likelihood framework for incorporation of prior images in CT reconstruction. Phys Med Biol [Internet]. 2013 [cited 2014 Nov 18];58(21):7563–7582. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3868341&tool=pmcentrez&rendertype=abstract.
  20. 20.
    Gang GJ, Stayman JW, Ehtiati T, Siewerdsen JH. Task-driven image acquisition and reconstruction in cone-beam CT. Phys Med Biol [Internet]. 2015;60(8):3129–50. Available from: http://stacks.iop.org/0031-9155/60/i=8/a=3129?key=crossref.408e80cb449d4c28561d7a6c7f5688c8.CrossRefGoogle Scholar
  21. 21.
    Tilley S, Siewerdsen JH, Stayman JW. Model-based iterative reconstruction for flat-panel cone-beam CT with focal spot blur, detector blur, and correlated noise. Phys Med Biol [Internet]. 2016;61(1):296–319. Available from: http://stacks.iop.org/0031-9155/61/i=1/a=296?key=crossref.4796deaf6827d354399470d1f41a47dc.PubMedCrossRefGoogle Scholar
  22. 22.
    Heiland M, Schulze D, Adam G, Schmelzle R. 3D-imaging of the facial skeleton with an isocentric mobile C-arm system (Siremobil Iso-C 3D ). Dentomaxillofacial Radiol [Internet]. 2003;32(1):21–5. Available from: http://www.birpublications.org/doi/10.1259/dmfr/80391180.CrossRefGoogle Scholar
  23. 23.
    Zhang J, Weir V, Fajardo L, Lin J, Hsiung H, Ritenour ER. Dosimetric characterization of a cone-beam O-arm imaging system. J Xray Sci Technol [Internet]. 2009;17(4):305–17. Available from: http://www.ncbi.nlm.nih.gov/pubmed/19923687.Google Scholar
  24. 24.
    Ritschl L, Kuntz J, Fleischmann C, Kachelrieß M. The rotate-plus-shift C-arm trajectory. Part I. complete data with less than 180° rotation. Med Phys [Internet]. 2016 12;43(5):2295–2302. Available from: http://doi.wiley.com/10.1118/1.4944785.PubMedCrossRefGoogle Scholar
  25. 25.
    Sheth NM, Zbijewski W, Jacobson MW, Abiola G, Kleinszig G, Vogt S, et al. Mobile C-arm with a CMOS detector: technical assessment of fluoroscopy and cone-beam CT imaging performance. Med Phys [Internet]. 2018;45(12):5420–36. Available from: https://onlinelibrary.wiley.com/doi/abs/10.1002/mp.13244.CrossRefGoogle Scholar
  26. 26.
    Chen B, Ning R. Cone-beam volume CT breast imaging: feasibility study. Med Phys [Internet]. 2002;29(5):755–70. Available from: http://doi.wiley.com/10.1118/1.1461843.CrossRefGoogle Scholar
  27. 27.
    Jaffray DA, Siewerdsen JH. Cone-beam computed tomography with a flat-panel imager: initial performance characterization. Med Phys [Internet]. 2000 [cited 2014 May 27];27(6):1311–1323. Available from: http://www.ncbi.nlm.nih.gov/pubmed/10902561.PubMedCrossRefGoogle Scholar
  28. 28.
    Fahrig R, Holdsworth DW. Three-dimensional computed tomographic reconstruction using a C-arm mounted XRII: image-based correction of gantry motion nonidealities. Med Phys [Internet]. 2000;27(1):30–8. Available from: http://doi.wiley.com/10.1118/1.598854.CrossRefGoogle Scholar
  29. 29.
    Arai Y, Honda K, Iwai K, Shinoda K. Practical model “3DX” of limited cone-beam X-ray CT for dental use. Int Congr Ser [Internet]. 2001;1230:713–8. Available from: http://linkinghub.elsevier.com/retrieve/pii/S0531513101001194.CrossRefGoogle Scholar
  30. 30.
    Hu H, He HD, Foley WD, Fox SH. Four multidetector-row helical CT: image quality and volume coverage speed. Radiology [Internet]. 2000;215(1):55–62. Available from: http://pubs.rsna.org/doi/10.1148/radiology.215.1.r00ap3755.PubMedCrossRefPubMedCentralGoogle Scholar
  31. 31.
    Pan X, Siewerdsen J, La Riviere PJ, Kalender WA. Anniversary paper: development of x-ray computed tomography: the role of medical physics and AAPM from the 1970s to present. Med Phys [Internet]. 2008;35(8):3728–39. Available from: http://doi.wiley.com/10.1118/1.2952653.CrossRefGoogle Scholar
  32. 32.
    Xu J, Sisniega A, Zbijewski W, Dang H, Stayman JW, Mow M, et al. Technical assessment of a prototype cone-beam CT system for imaging of acute intracranial hemorrhage. Med Phys. 2016;43(10):5745.PubMedCrossRefPubMedCentralGoogle Scholar
  33. 33.
    Gang GJ, Zbijewski W, Mahesh M, Thawait G, Packard N, Yorkston J, et al. Image quality and dose for a multisource cone-beam CT extremity scanner. Med Phys [Internet]. 2018;45(1):144–55. Available from: http://www.ncbi.nlm.nih.gov/pubmed/29121409.CrossRefGoogle Scholar
  34. 34.
    Flohr TG, McCollough CH, Bruder H, Petersilka M, Gruber K, Süβ C, et al. First performance evaluation of a dual-source CT (DSCT) system. Eur Radiol [Internet]. 2006;16(2):256–68. Available from: http://link.springer.com/10.1007/s00330-005-2919-2.PubMedCrossRefGoogle Scholar
  35. 35.
    Siewerdsen JH, Jaffray DA. Cone-beam computed tomography with a flat-panel imager: magnitude and effects of x-ray scatter. Med Phys [Internet]. 2001;28(2):220–31. Available from: http://doi.wiley.com/10.1118/1.1339879.CrossRefGoogle Scholar
  36. 36.
    Schafer S, Stayman JW, Zbijewski W, Schmidgunst C, Kleinszig G, Siewerdsen JH. Antiscatter grids in mobile C-arm cone-beam CT: effect on image quality and dose. Med Phys [Internet]. 2012 [cited 2014 May 27];39(1):153–159. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3261054&tool=pmcentrez&rendertype=abstract.
  37. 37.
    Siewerdsen JH, Moseley DJ, Bakhtiar B, Richard S, Jaffray DA. The influence of antiscatter grids on soft-tissue detectability in cone-beam computed tomography with flat-panel detectors. Med Phys [Internet]. 2004. [cited 2014 May 27];31;(12):3506–20.. Available from: http://www.ncbi.nlm.nih.gov/pubmed/15651634 PubMedCrossRefGoogle Scholar
  38. 38.
    Sisniega A, Zbijewski W, Badal A, Kyprianou IS, Stayman JW, Vaquero JJ, et al. Monte Carlo study of the effects of system geometry and antiscatter grids on cone-beam CT scatter distributions. Med Phys [Internet]. 2013 [cited 2014 May 27];40(5):051915. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3651212&tool=pmcentrez&rendertype=abstract.
  39. 39.
    Weir VJ, Zhang J, Bruner AP. Dosimetric characterization and image quality evaluation of the AIRO mobile CT scanner. J Xray Sci Technol [Internet]. 2015;23(3):373–81. Available from: www.pubmedcentral.nih.gov/articlerender=iospress&doi=10.3233/XST-150496.Google Scholar
  40. 40.
    Barsa P, Frőhlich R, Beneš V, Suchomel P. Intraoperative portable CT-scanner based spinal navigation – a feasibility and safety study. Acta Neurochir (Wien) [Internet]. 2014;156(9):1807–12. Available from: http://link.springer.com/10.1007/s00701-014-2184-8.CrossRefGoogle Scholar
  41. 41.
    Katsevich A. Analysis of an exact inversion algorithm for spiral cone-beam CT. Phys Med Biol [Internet]. 2002;47(15):302. Available from: http://stacks.iop.org/0031-9155/47/i=15/a=302?key=crossref.a6eb76dffee2c2ce17372b064074320b.Google Scholar
  42. 42.
    Siewerdsen JH, Daly MJ, Bachar G, Moseley DJ, Bootsma G, Brock KK, et al. Multimode C-arm fluoroscopy, tomosynthesis, and cone-beam CT for image-guided interventions: from proof of principle to patient protocols. In: Hsieh J, Flynn MJ, editors. Proc SPIE [Internet]. 2007 [cited 2014 Jul 17];6510:65101A–65101A–11. Available from: http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1299299.
  43. 43.
    Wang AS, Stayman JW, Otake Y, Kleinszig G, Vogt S, Gallia GL, et al. Soft-tissue imaging with C-arm cone-beam CT using statistical reconstruction. Phys Med Biol [Internet]. 2014 [cited 2014 May 27];59(4):1005–1026. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4046706&tool=pmcentrez&rendertype=abstract.
  44. 44.
    Prakash P, Zbijewski W, Gang GJ, Ding Y, Stayman JW, Yorkston J, et al. Task-based modeling and optimization of a cone-beam CT scanner for musculoskeletal imaging. Med Phys [Internet]. 2011 [cited 2014 May 27];38(10):5612–5629. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3208412&tool=pmcentrez&rendertype=abstract.
  45. 45.
    Dang H, Stayman JW, Sisniega A, Xu J, Zbijewski W, Wang X, et al. Statistical reconstruction for cone-beam CT with a post-artifact-correction noise model: application to high-quality head imaging. Phys Med Biol [Internet]. 2015 [cited 2015 Aug 18];60(16):6153–6175. Available from: http://www.ncbi.nlm.nih.gov/pubmed/26225912.PubMedPubMedCentralCrossRefGoogle Scholar
  46. 46.
    Dang H, Stayman JW, Xu J, Zbijewski W, Sisniega A, Mow M, et al. Task-based statistical image reconstruction for high-quality cone-beam CT. Phys Med Biol. 2017;62(22):8693–719.PubMedCrossRefPubMedCentralGoogle Scholar
  47. 47.
    Dang H, Stayman JW, Sisniega A, Zbijewski W, Xu J, Wang X, et al. Multi-resolution statistical image reconstruction for mitigation of truncation effects: application to cone-beam CT of the head. Phys Med Biol. 2017;62(2):539–59.PubMedCrossRefPubMedCentralGoogle Scholar
  48. 48.
    Sisniega A, Zbijewski W, Xu J, Dang H, Stayman JW, Yorkston J, et al. High-fidelity artifact correction for cone-beam CT imaging of the brain. Phys Med Biol [Internet]. 2015 [cited 2015 Jan 29];60(4):1415–1439. Available from: http://www.ncbi.nlm.nih.gov/pubmed/25611041.PubMedCrossRefPubMedCentralGoogle Scholar
  49. 49.
    Defrise M, Clack R. A cone-beam reconstruction algorithm using shift-variant filtering and cone-beam backprojection. IEEE Trans Med Imaging [Internet]. 1994;13(1):186–95.. Available from: http://ieeexplore.ieee.org/document/276157/ CrossRefGoogle Scholar
  50. 50.
    Daly MJ, Siewerdsen JH, Moseley DJ, Jaffray DA, Irish JC. Intraoperative cone-beam CT for guidance of head and neck surgery: assessment of dose and image quality using a C-arm prototype. Med Phys [Internet]. 2006 [cited 2014 May 27];33(10):3767–3780. Available from: http://www.ncbi.nlm.nih.gov/pubmed/17089842.PubMedCrossRefGoogle Scholar
  51. 51.
    Hernandez AM, Schwoebel P, Boone JM, Becker A. Multisource x-ray system for artifact reduction in dedicated breast CT. In: Krupinski EA, editor. 14th International Workshop on Breast Imaging (IWBI 2018) [Internet]. SPIE; 2018. p. 19. Available from: https://www.spiedigitallibrary.org/conference-proceedings-of-spie/10718/2317846/Multisource-x-ray-system-for-artifact-reduction-in-dedicated-breast/10.1117/12.2317846.full.
  52. 52.
    Xu J. Evaluation of detector readout gain mode and bowtie filters for cone-beam CT imaging of the head. Phys Med Biol [Internet]. 2016;61(16):5973–5992(20). Available from: http://www.ncbi.nlm.nih.gov/pubmed/?term=Evaluation+of+detector+readout+gain+mode+and+bowtie+filters+for+cone-beam+CT+imaging+of+the+head.PubMedCrossRefGoogle Scholar
  53. 53.
    Stayman JW. Fluence-field modulated x-ray CT using multiple aperture devices. Proc Soc Photo Opt Instrum Eng [Internet]. 2016. Available from: http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=2506547.
  54. 54.
    El-Mohri Y, Antonuk LE, Koniczek M, Zhao Q, Li Y, Street RA, et al. Active pixel imagers incorporating pixel-level amplifiers based on polycrystalline-silicon thin-film transistors. Med Phys [Internet]. 2009;36(7):3340–55. Available from: http://doi.wiley.com/10.1118/1.3116364.CrossRefGoogle Scholar
  55. 55.
    Stavro J, Goldan AH, Zhao W. SWAD: inherent photon counting performance of amorphous selenium multi-well avalanche detector. In: Kontos D, Flohr TG, Lo JY, editors. 2016. p. 97833Q. Available from: http://proceedings.spiedigitallibrary.org/proceeding.aspx?doi=10.1117/12.2217248.
  56. 56.
    Pickhardt PJ, Lubner MG, Kim DH, Tang J, Ruma JA, del Rio AM, et al. Abdominal CT with model-based iterative reconstruction (MBIR): initial results of a prospective trial comparing ultralow-dose with standard-dose imaging. Am J Roentgenol [Internet]. 2012;199(6):1266–74. Available from: http://www.ajronline.org/doi/10.2214/AJR.12.9382.CrossRefGoogle Scholar
  57. 57.
    Chen H, Zhang Y, Kalra MK, Lin F, Chen Y, Liao P, et al. Low-dose CT with a residual encoder-decoder convolutional neural network. IEEE Trans Med Imaging [Internet]. 2017;36(12):2524–35. Available from: https://ieeexplore.ieee.org/document/7947200/.PubMedPubMedCentralCrossRefGoogle Scholar
  58. 58.
    Li Z, Yu L, Trzasko JD, Lake DS, Blezek DJ, Fletcher JG, et al. Adaptive nonlocal means filtering based on local noise level for CT denoising. Med Phys [Internet]. 2013 Dec 31;41(1):011908. Available from: http://doi.wiley.com/10.1118/1.4851635.CrossRefGoogle Scholar
  59. 59.
    Lindfors KK, Boone JM, Nelson TR, Yang K, Kwan ALC, Miller DF. Dedicated breast CT: Initial clinical experience. Radiology [Internet]. 2008;246(3):725–33. Available from: http://pubs.rsna.org/doi/10.1148/radiol.2463070410.CrossRefGoogle Scholar
  60. 60.
    Kwan ALC, Boone JM, Yang K, Huang S-Y. Evaluation of the spatial resolution characteristics of a cone-beam breast CT scanner. Med Phys [Internet]. 2006;34(1):275–81. Available from: http://doi.wiley.com/10.1118/1.2400830.CrossRefGoogle Scholar
  61. 61.
    Zhao B, Zhang X, Cai W, Conover D, Ning R. Cone beam breast CT with multiplanar and three dimensional visualization in differentiating breast masses compared with mammography. Eur J Radiol [Internet]. 2015;84(1):48–53. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0720048X14002903.CrossRefGoogle Scholar
  62. 62.
    Thawait GK, Demehri S, AlMuhit A, Zbijweski W, Yorkston J, Del Grande F, et al. Extremity cone-beam CT for evaluation of medial tibiofemoral osteoarthritis: initial experience in imaging of the weight-bearing and non-weight-bearing knee. Eur J Radiol [Internet]. 2015 [cited 2015 Nov 19]; Available from: http://www.ncbi.nlm.nih.gov/pubmed/26388464.
  63. 63.
    Demehri S, Muhit A, Zbijewski W, Stayman JW, Yorkston J, Packard N, et al. Assessment of image quality in soft tissue and bone visualization tasks for a dedicated extremity cone-beam CT system. Eur Radiol [Internet]. 2015 25(6):1742–1751 [cited 2015 Apr 17]; Available from: http://www.ncbi.nlm.nih.gov/pubmed/25599933.PubMedCrossRefGoogle Scholar
  64. 64.
    de Cesar NC, Schon LC, Thawait GK, da Fonseca LF, Chinanuvathana A, Zbijewski WB, et al. Flexible adult acquired flatfoot deformity. J Bone Jt Surg [Internet]. 2017;99(18):e98. Available from: http://insights.ovid.com/crossref?an=00004623-201709200-00015.CrossRefGoogle Scholar
  65. 65.
    Sisniega A, Xu J, Dang H, Zbijewski W, Stayman JW, Mow M, et al. In: Flohr TG, Lo JY, Gilat Schmidt T, editors. Development and clinical translation of a cone-beam CT scanner for high-quality imaging of intracranial hemorrhage. Orlando: SPIE; 2017. p. 101320K.Google Scholar
  66. 66.
    Kalender WA, Kolditz D, Steiding C, Ruth V, Lück F, Rößler A-C, et al. Technical feasibility proof for high-resolution low-dose photon-counting CT of the breast. Eur Radiol [Internet]. 2017;27(3):1081–6. Available from: http://link.springer.com/10.1007/s00330-016-4459-3.CrossRefGoogle Scholar
  67. 67.
    John S, Stock S, Cerejo R, Uchino K, Winners S, Russman A, et al. Brain imaging using Mobile CT: current status and future prospects. J Neuroimaging [Internet]. 2016;26(1):5–15. Available from: http://doi.wiley.com/10.1111/jon.12319.CrossRefGoogle Scholar
  68. 68.
    Siewerdsen JH, Sisniega A, Zbijewski W, Wu P, Stayman JW, Koliatsos VE, et al. Image quality, scatter, and dose in compact CBCT systems with flat and curved detectors. In: Chen G-H, Lo JY, Gilat Schmidt T, editors. Medical imaging 2018: physics of medical imaging [internet]. Orlando: SPIE; 2018. p. 163. Available from: https://www.spiedigitallibrary.org/conference-proceedings-of-spie/10573/2293872/Image-quality-scatter-and-dose-in-compact-CBCT-systems-with/10.1117/12.2293872.full.CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Biomedical EngineeringJohns Hopkins UniversityBaltimoreUSA

Personalised recommendations