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Detection and localization of hyperfunctioning parathyroid glands on [18F]fluorocholine PET/ CT using deep learning – model performance and comparison to human experts
Authors
Leon Jarabek
Department of Radiology, General Hospital Novo Mesto, Novo Mesto, Slovenia
Jan Jamsek
Department for Nuclear Medicine, University Medical Centre, Ljubljana, Slovenia
Anka Cuderman
Department for Nuclear Medicine, University Medical Centre, Ljubljana, Slovenia
Sebastijan Rep
Department for Nuclear Medicine, University Medical Centre, Ljubljana, Slovenia
Faculty of Health Sciences, University of Ljubljana, Ljubljana, Slovenia
Marko Hocevar
Department of Surgical Oncology, Institute of Oncology, Ljubljana, Slovenia
Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
Tomaz Kocjan
Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
Department for Endocrinology, Diabetes and Metabolic Diseases, University Medical Centre, Ljubljana, Slovenia
Mojca Jensterle
Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
Department for Endocrinology, Diabetes and Metabolic Diseases, University Medical Centre, Ljubljana, Slovenia
Ziga Spiclin
Faculty of Electrical Engineering, University of Ljubljana, Ljubljana, Slovenia
Ziga Macek Lezaic
Rožna dolina, Ljubljana, Slovenia
Filip Cvetko
Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
Luka Lezaic
Department for Nuclear Medicine, University Medical Centre, Ljubljana, Slovenia
Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
Language: English
Page range: 440 - 452
Submitted on: Apr 21, 2022
Accepted on: Aug 22, 2022
Published on: Dec 13, 2022
Published by: Association of Radiology and Oncology
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Related subjects:
© 2022 Leon Jarabek, Jan Jamsek, Anka Cuderman, Sebastijan Rep, Marko Hocevar, Tomaz Kocjan, Mojca Jensterle, Ziga Spiclin, Ziga Macek Lezaic, Filip Cvetko, Luka Lezaic, published by Association of Radiology and Oncology
This work is licensed under the Creative Commons Attribution 4.0 License.