Hardware Developments for Radiation Dose Reduction

  • Rich Mather
Part of the Medical Radiology book series (MEDRAD)


The evolution of CT has created systems that scan faster, use thinner sections, and cover more patient anatomy in a single rotation. These developments have not only opened the spectrum of CT applications but have also driven the need for new methods of radiation dose reduction. By analyzing the imaging chain from X-ray tubes and collimators to detectors and data acquisition systems, we examine the various hardware-based dose reduction strategies in the modern CT system. As part of a concerted effort between clinicians, physicists, and manufacturers, hardware innovation and system design play a significant role in optimizing the radiation dose in CT.


Iterative Reconstruction Patient Dose Iterative Reconstruction Algorithm Optimize Image Quality Adaptive Iterative Dose Reduction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Achenbach S, Ropers D, Pohle K et al (2003) Clinical results of minimally invasive coronary angiography using computed tomography. Cardiol Clin 21:549–559PubMedCrossRefGoogle Scholar
  2. Bushberg JT, Seibert JA, Leidholdt EM, Boone III JM (2002) Ch 13 Computed Tomography. In: The essential physics of medical imaging, 2nd edn. Lipincott Williams and Wilkins, pp 367–369Google Scholar
  3. Bardo DM, Asamato J, Mackay CS, Minette M (2009) Low-dose coronary artery computed tomography angiogram of an infant with tetralogy of fallot using a 256-slice multidetector computed tomography scanner. Pediatr Cardiol 30:824–826PubMedCrossRefGoogle Scholar
  4. Deak PD, Langner O, Lell M, Kalender WA (2009) Effects of adaptive section collimation on patient radiation dose in multisection spiral CT. Radiology 252:140–147PubMedCrossRefGoogle Scholar
  5. Flohr TG, Leng S, Yu L et al (2009) Dual-source spiral CT with pitch up to 3.2 and 75 ms temporal resolution: image reconstruction and assessment of image quality. Med Phys 36:5641–5653PubMedCrossRefGoogle Scholar
  6. Lin XZ, Miao F, Li JY et al (2011) High-definition CT Gemstone spectral imaging of the brain: initial results of selecting optimal monochromatic image for beam-hardening artifacts and image noise reduction. J Comput Assist Tomogr 35:294–297PubMedCrossRefGoogle Scholar
  7. Mastora I, Remy-Jardin M, Suess C et al (2001) Dose reduction in spiral CT angiography of thoracic outlet syndrome by anatomically adapted tube current modulation. Eur Radiol 11:590–596PubMedCrossRefGoogle Scholar
  8. Mahesh M (2002) Search for isotropic resolution in CT from conventional through multiple-row detector. Radiographics 22:949–962PubMedGoogle Scholar
  9. Okumura M, Tamatani M, Igarishi K (2002) Development of X-ray Detector for Multi-slice CT with 0.5 mm. Slice thickness and 0.5 second revolution. Proc SPIE 4682:14Google Scholar
  10. Rybicki FJ, Otero HJ, Steigner ML et al (2008) Initial evaluation of coronary images from 320-detector row computed tomography. Int J Cardiovasc Imaging 24:535–546PubMedCrossRefGoogle Scholar
  11. Seeram E (2001) Computed tomography: physical principles, clinical applications, and quality control. 2nd edn. Saunders, PhiladelphiaGoogle Scholar
  12. Szulc M, Judy PF (1979) Effect of X-ray filtration on dose and image performance of CT scanners. Med Phys 6:479–486PubMedCrossRefGoogle Scholar
  13. Tzedakis A, Damilakis J, Perisinakis K et al (2005) The effect of z overscanning on patient effective dose from multidetector helical computed tomography examinations. Med Phys 32:1621–1629PubMedCrossRefGoogle Scholar
  14. van der Molen AJ, Geleijns J (2007) Overranging in multisection CT: quantification and relative contribution to dose–comparison of four 16-section CT scanners. Radiology 242:208–216PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  1. 1.Toshiba Medical Research InstituteVernon HillsUSA

Personalised recommendations