A student trained convolutional neural network competing with a commercial AI software and experts in organ at risk segmentation.

Humans Neural Networks, Computer Prostatic Neoplasms / radiotherapy Male Organs at Risk Retrospective Studies Software Artificial Intelligence Radiotherapy Planning, Computer-Assisted / methods Urinary Bladder / diagnostic imaging Positron Emission Tomography Computed Tomography Rectum / diagnostic imaging
Artificial intelligence Auto segmentation Convolutional neural network Prostate cancer Radiation treatment planning Turing test

Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
29 10 2024
Historique:
received: 11 05 2024
accepted: 11 10 2024
medline: 30 10 2024
pubmed: 30 10 2024
entrez: 30 10 2024
Statut: epublish

Résumé

This retrospective, multi-centered study aimed to improve high-quality radiation treatment (RT) planning workflows by training and testing a Convolutional Neural Network (CNN) to perform auto segmentations of organs at risk (OAR) for prostate cancer (PCa) patients, specifically the bladder and rectum. The objective of this project was to develop a clinically applicable and robust artificial intelligence (AI) system to assist radiation oncologists in OAR segmentation. The CNN was trained using manual contours in CT-datasets from diagnostic

Identifiants

DOI: 10.1038/s41598-024-76288-y PMID: 39472608
pubmed: 39472608
doi: 10.1038/s41598-024-76288-y
pii: 10.1038/s41598-024-76288-y
doi:

Types de publication

Journal Article Multicenter Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

25929

Informations de copyright

© 2024. The Author(s).

Références

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Auteurs

Sophia L Bürkle (SL)

Department of Radiation Oncology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany. sophia.buerkle@uniklinik-freiburg.de.

Dejan Kuhn (D)

Division of Medical Physics, Department of Radiation Oncology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.

Tobias Fechter (T)

Division of Medical Physics, Department of Radiation Oncology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany.

Gianluca Radicioni (G)

Department of Radiation Oncology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.

Nanna Hartong (N)

Department of Radiation Oncology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.

Martin T Freitag (MT)

Department of Nuclear Medicine, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.

Xuefeng Qiu (X)

Department of Urology, Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China.

Efstratios Karagiannis (E)

German Oncology Center (GOC), European University of Cyprus, Limassol, Cyprus.

Anca-Ligia Grosu (AL)

Department of Radiation Oncology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany.

Dimos Baltas (D)

Division of Medical Physics, Department of Radiation Oncology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany.

Constantinos Zamboglou (C)

Department of Radiation Oncology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany.
German Oncology Center (GOC), European University of Cyprus, Limassol, Cyprus.
Berta-Ottenstein-Programme, Faculty of Medicine, University of Freiburg, Freiburg, Germany.

Simon K B Spohn (SKB)

Department of Radiation Oncology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany.
Berta-Ottenstein-Programme, Faculty of Medicine, University of Freiburg, Freiburg, Germany.

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Classifications MeSH

questionsmedicales.fr › Eucaryotes › Animaux › Chordés › Vertébrés › Mammifères › Eutheria › Primates › Haplorhini › Catarrhini › Hominidae › Humains › A student trained convolutional neural network...
questionsmedicales.fr › Sciences de l'information › Méthodologies informatiques › Algorithmes › Intelligence artificielle › Réseaux neuronaux (ordinateur) › A student trained convolutional neural network...
questionsmedicales.fr › Maladies urogénitales › Tumeurs de l'appareil urogénital › Tumeurs de l'appareil génital mâle › Tumeurs de la prostate › A student trained convolutional neural network...
questionsmedicales.fr › Régions du corps › Organes à risque › A student trained convolutional neural network...
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questionsmedicales.fr › Sciences de l'information › Méthodologies informatiques › Algorithmes › Intelligence artificielle › A student trained convolutional neural network...
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questionsmedicales.fr › Appareil urogénital › Voies urinaires › Vessie urinaire › A student trained convolutional neural network...
questionsmedicales.fr › Diagnostic › Techniques et procédures diagnostiques › Techniques de diagnostic radioisotopique › Scintigraphie › Tomoscintigraphie › Tomographie par émission de positons › Tomographie par émission de positons couplée à la tomodensitométrie › A student trained convolutional neural network...
questionsmedicales.fr › Système digestif › Tube digestif › Tube digestif inférieur › Gros intestin › Rectum › A student trained convolutional neural network...