Development and Validation of an Algorithm for Segmentation of the Prostate and its Zones from Three-dimensional Transrectal Multiparametric Ultrasound Images.

Journal: European urology open science
Published Date: Apr 6, 2025

Abstract

BACKGROUND AND OBJECTIVE: Multiparametric ultrasound (mpUS) is being investigated as an alternative to magnetic resonance imaging (MRI) for detection of prostate cancer (PC). Automated prostate segmentation facilitates workflows, and zonal segmentation can aid in PC diagnosis, accounting for differences in imaging characteristics and tumor incidence. Our aim was to develop a deep learning algorithm that can automatically segment the prostate and its zones on three-dimensional (3D) contrast-enhanced ultrasound (CEUS) and conventional brightness-mode (B-mode) images (NCT04605276).

Authors

  • Daniel L van den Kroonenberg
    Department of Urology, Amsterdam UMC, Amsterdam, The Netherlands.
  • Florian T Delberghe
    Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
  • Auke Jager
    Department of Urology, Amsterdam UMC, Amsterdam, The Netherlands.
  • Arnoud W Postema
    Department of Urology, Leiden University Medical Center, Leiden, The Netherlands.
  • Harrie P Beerlage
    Department of Urology, Amsterdam University Medical Centers (Amsterdam UMC), University of Amsterdam, Amsterdam, The Netherlands.
  • Wim Zwart
    Angiogenesis Analytics, JADS Venture Campus, 's-Hertogenbosch, The Netherlands.
  • Massimo Mischi
    Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
  • Jorg R Oddens
    Department of Urology, Amsterdam UMC, Amsterdam, The Netherlands.

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