Comparison of data fusion strategies for automated prostate lesion detection using mpMRI correlated with whole mount histology.

Journal: Radiation oncology (London, England)
Published Date: Jul 29, 2024

Abstract

BACKGROUND: In this work, we compare input level, feature level and decision level data fusion techniques for automatic detection of clinically significant prostate lesions (csPCa).

Authors

  • Deepa Darshini Gunashekar
    Department of Radiology, Medical Physics, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
  • Lars Bielak
    Department of Radiology, Medical Physics, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany. lars.bielak@uniklinik-freiburg.de.
  • Benedict Oerther
    Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
  • Matthias Benndorf
    Department of Radiology, Faculty of Medicine, University of Freiburg Medical Centre, Freiburg, Germany.
  • Andrea Nedelcu
    Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
  • Samantha Hickey
    Division of Medical Physics, Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
  • Constantinos Zamboglou
    German Cancer Consortium (DKTK), Partner Site Freiburg, Germany constantinos.zamboglou@uniklinik-freiburg.de.
  • Anca-Ligia Grosu
    German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany.
  • Michael Bock
    Department of Radiology, Medical Physics, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.

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