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

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

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. Methods: Our...

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Bibliographic Details
Main Authors: Suleiman Abuhasanein, Lars Edenbrandt, Olof Enqvist, Staffan Jahnson, Henrik Leonhardt, Elin Trägårdh, Johannes Ulén, Henrik Kjölhede
Format: Article
Language:English
Published: Medical journals sweden AB 2024-05-01
Series:Scandinavian Journal of Urology
Subjects:
Artificial intelligence
bladder cancer
computed tomography
convolutional neural networks
hematuria
Online Access:https://medicaljournalssweden.se/SJU/article/view/39930
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