Article thumbnail
Location of Repository

New technologies to reduce pediatric radiation doses

By Philipp Bernhardt, Markus Lendl and Frank Deinzer

Abstract

X-ray dose reduction in pediatrics is particularly important because babies and children are very sensitive to radiation exposure. We present new developments to further decrease pediatric patient dose. With the help of an advanced exposure control, a constant image quality can be maintained for all patient sizes, leading to dose savings for babies and children of up to 30%. Because objects of interest are quite small and the speed of motion is high in pediatric patients, short pulse widths down to 4 ms are important to reduce motion blurring artifacts. Further, a new noise-reduction algorithm is presented that detects and processes signal and noise in different frequency bands, generating smooth images without contrast loss. Finally, we introduce a super-resolution technique: two or more medical images, which are shifted against each other in a subpixel region, are combined to resolve structures smaller than the size of a single pixel. Advanced exposure control, short exposure times, noise reduction and super-resolution provide improved image quality, which can also be invested to save radiation exposure. All in all, the tools presented here offer a large potential to minimize the deterministic and stochastic risks of radiation exposure

Topics: Alara
Publisher: Springer-Verlag
OAI identifier: oai:pubmedcentral.nih.gov:2663645
Provided by: PubMed Central

Suggested articles

Citations

  1. (2003). A nonlinear multiresolution gradient adaptive filter for medical images.
  2. (2004). Advances and challenges in super-resolution (invited paper).
  3. (2004). Fast and robust multi-frame super-resolution.
  4. (2005). Spatial frequency-dependent signal-to-noise ratio as a generalized measure of image quality.
  5. (1990). Super resolution from image sequences.
  6. (2001). Superresolution in MRI: application to human white matter fiber tract visualization by diffusion tensor imaging.
  7. (1983). The Laplacian pyramid as a compact image code.

To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.