A CT deep learning reconstruction algorithm: Image quality evaluation for brain protocol at decreasing dose indexes in comparison with FBP and statistical iterative reconstruction algorithms.

Journal: Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Published Date: Feb 28, 2024

Abstract

PURPOSE: To characterise the impact of Precise Image (PI) deep learning reconstruction algorithm on image quality, compared to filtered back-projection (FBP) and iDose iterative reconstruction for brain computed tomography (CT) phantom images.

Authors

  • Silvia Tomasi
    Department of Medical Physics, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy; Medical Physics Specialization School, Alma Master Studiorium, University of Bologna, Bologna, Italy.
  • Klarisa Elena Szilagyi
    Department of Medical Physics, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
  • Patrizio Barca
    Department of Medical Physics, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy. Electronic address: patrizio.barca@ao-pisa.toscana.it.
  • Francesca Bisello
    Department of Medical Physics, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
  • Lorenzo Spagnoli
    Department of Medical Physics, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy; Medical Physics Specialization School, Alma Master Studiorium, University of Bologna, Bologna, Italy.
  • Sara Domenichelli
    Department of Medical Physics, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
  • Lidia Strigari
    IRCCS Azienda Ospedaliera Universitaria di Bologna, Medical Physics Department, Bologna, Italy. Electronic address: lidia.strigari@aosp.bo.it.

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