Deep learning-based self-supervised detection and localization of magnetic resonance imaging anomalies in artificial intelligence-supported radiotherapy workflows
- DOI
- 10.1016/j.phro.2026.101114
- Published
- 2026-11
- Container
- Physics and Imaging in Radiation Oncology
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.phro.2026.101114,
title = {Deep learning-based self-supervised detection and localization of magnetic resonance imaging anomalies in artificial intelligence-supported radiotherapy workflows},
author = {Mustafa Kadhim and Viktor Rogowski and Emilia Persson and Camila Gonzalez and André Haraldsson and Sofie Ceberg and Mikael Nilsson and Malin Kügele and Sven Bäck and Christian Jamtheim Gustafsson},
year = {2026},
journal = {Physics and Imaging in Radiation Oncology},
doi = {10.1016/j.phro.2026.101114},
url = {https://doi.org/10.1016/j.phro.2026.101114}
}RIS
TY - JOUR TI - Deep learning-based self-supervised detection and localization of magnetic resonance imaging anomalies in artificial intelligence-supported radiotherapy workflows AU - Mustafa Kadhim AU - Viktor Rogowski AU - Emilia Persson AU - Camila Gonzalez AU - André Haraldsson AU - Sofie Ceberg AU - Mikael Nilsson AU - Malin Kügele AU - Sven Bäck AU - Christian Jamtheim Gustafsson PY - 2026 JO - Physics and Imaging in Radiation Oncology DO - 10.1016/j.phro.2026.101114 UR - https://doi.org/10.1016/j.phro.2026.101114 ER -
APA
Kadhim, M., Rogowski, V., Persson, E., Gonzalez, C., Haraldsson, A., Ceberg, S., Nilsson, M., Kügele, M., Bäck, S., & Gustafsson, C. J. (2026). Deep learning-based self-supervised detection and localization of magnetic resonance imaging anomalies in artificial intelligence-supported radiotherapy workflows. Physics and Imaging in Radiation Oncology. https://doi.org/10.1016/j.phro.2026.101114
Source records
- crossref · retrieved 2026-11-09T20:18:03.319Z