A novel model of artificial intelligence based automated image analysis of CT urography to identify bladder cancer in patients investigated for macroscopic hematuria.

Journal: Scandinavian journal of urology
PMID: 38698545

Abstract

OBJECTIVE: To evaluate whether artificial intelligence (AI) based automatic image analysis utilising convolutional neural networks (CNNs) can be used to evaluate computed tomography urography (CTU) for the presence of urinary bladder cancer (UBC) in patients with macroscopic hematuria.

Authors

  • Suleiman Abuhasanein
    Department of Urology, Institute of Clinical Science, Sahlgrenska Academy, University of Gothenburg, Göteborg, Sweden; Department of Surgery, Urology section, NU Hospital Group, Uddevalla, Region Västra Götaland, Sweden. suleiman.abuhasanein@gmail.com.
  • Lars Edenbrandt
    Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
  • Olof Enqvist
    Department of Electrical Engineering, Region Västra Götaland, Chalmers University of Technology, Gothenburg, Sweden.
  • Staffan Jahnson
    Division of Urology, Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden.
  • Henrik Leonhardt
    Department of Radiology, Institute of Clinical Science, Sahlgrenska Academy, University of Gothenburg, Göteborg, Sweden; Department of Radiology, Sahlgrenska University Hospital, Region Västra Götaland, Göteborg, Sweden.
  • Elin Trägårdh
    Department of Clinical Physiology and Nuclear Medicine, Lund University and Skåne University Hospital, Malmö, Sweden.
  • Johannes Ulén
    Eigenvision AB, Malmö, Sweden.
  • Henrik Kjölhede
    Department of Urology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.

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