Radon space dose optimization in repeat CT scanning

N. Shamul*, L. Joskowicz

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


We present a new method for on-line radiation dose optimization in repeat computer tomography (CT) scanning. Our method uses the information of the baseline scan during the repeat scanning to significantly reduce the radiation dose without compromising the repeat scan quality. It automatically registers the patient to the baseline scan using fractional scanning and detects in sinogram space the patient regions where changes have occurred without having to reconstruct the repeat scan image. It scans only these regions in the patient, thereby considerably reducing the necessary radiation dose. It then completes themissing values of the sparsely sampled repeat scan sinogram with those of the fully sampled baseline sinogram in regions where no changes were detected and computes the repeat scan image by standard filtered backprojection reconstruction. Experiments on a patient scan with simulated changes yield amean recall of 98% using <19% of a full dose. Experiments on real CT scans of an abdomen phantom produce similar results, with a mean recall of 94.5% and only 14.4% of a full dose more than the theoretical optimum. As hardly any changed rays are missed, the reconstructed images are practically indistinguishable from a full dose scan. Our method successfully detects small, low contrast changes and produces an accurate repeat scan reconstruction using three times less radiation than an image space baseline method.

Original languageAmerican English
Article number8023866
Pages (from-to)2436-2448
Number of pages13
JournalIEEE Transactions on Medical Imaging
Issue number12
StatePublished - Dec 2017

Bibliographical note

Publisher Copyright:
© 2017 IEEE.


  • Fractional CT scanning
  • Reduced dose CT scanning
  • Repeat CT scanning.


Dive into the research topics of 'Radon space dose optimization in repeat CT scanning'. Together they form a unique fingerprint.

Cite this