Polar pixel Kalman filter for limited data computed tomography (CT) image reconstruction

Michael H. Buonocore, William R. Brody, Albert Macovski, Sally L. Wood

Research output: Contribution to journalArticlepeer-review


Rapid cardiovascular computed tomography (CT) requires image reconstruction from a limited set of projections. Deterministic methods using convolution back projection algorithms have not been suitable for these limited data cases. An alternative approach has been formulated to find the minimum mean squared error image estimate using a Kalman filter with polar pixels for two-dimensional reconstructions of both simulated phantoms and real objects from data obtained on a rotate only CT scanner. Computation time was minimized by limiting the number of pixels to 120 and using a rotationally symmetric (polar) pixel structure. The Kalman filter was compared with Algebraic Reconstruction Technique (ART) for full view, limited view, and missing view measurement sets. The Kalman filter performed with consistently lower mean squared error than ART for both real and simulated data and rapidly converged to the theoretical limit of resolution. Performance of the Kalman filter was optimized only if the system noise (error) was adequately characterized. When real objects were scanned it was necessary to include the measurement errors introduced by finite pixel width and finite beam width in addition to Poisson noise to achieve optimality. The use of polar rather than rectangular pixels provided a reduction in computation and storage requirements for the Kalman filter. This study demonstrates the potential utility of Kalman filtering methods using polar pixels for limited data CT image reconstruction.

Original languageEnglish (US)
Pages (from-to)109-114
Number of pages6
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - Dec 26 1979
Externally publishedYes

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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