Sparse 3D radon space rigid registration of CT scans: Method and validation study

G. Medan, N. Shamul, L. Joskowicz*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Scopus citations


We present a new method for rigid registration of CT datasets in 3D Radon space based on sparse sampling of scanning projections. The inputs are the two 3D Radon transforms of the CT scans, one densely sampled and the other sparsely sampled (limited number of scan angles/ranges). The output is the rigid transformation that best matches them. The method first finds the best matching between each projection direction vector in the sparse transform and the corresponding direction vector in the dense transform. It then solves a system of linear equations derived from the direction vector pairs (parallel-beam projections) or finds a solution by non-linear optimization (fan-beam and cone-beam projections). Experimental studies show that our method for 3D parallel beam registration outperforms image space registration in terms of convergence range with significantly reduced X-ray dose compared to a full conventional CT scan.

Original languageAmerican English
Pages (from-to)497-506
Number of pages10
JournalIEEE Transactions on Medical Imaging
Issue number2
StatePublished - Feb 2017

Bibliographical note

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  • CT scanning
  • Radon transform
  • image processing
  • reduced-dose scanning
  • rigid registration


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