Anomaly detection in radiotherapy plans using deep autoencoder networks

PURPOSE: Treatment plans are used for patients under radiotherapy in clinics. Before execution, these plans are checked for safety and quality by human experts. A few of them were identified with flaws and needed further improvement. To automate this checking process, an unsupervised learning method...

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Detalles Bibliográficos
Autores principales: Huang, Peng, Shang, Jiawen, Xu, Yingjie, Hu, Zhihui, Zhang, Ke, Dai, Jianrong, Yan, Hui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10043249/
https://www.ncbi.nlm.nih.gov/pubmed/36998450
http://dx.doi.org/10.3389/fonc.2023.1142947

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10043249/
https://www.ncbi.nlm.nih.gov/pubmed/36998450
http://dx.doi.org/10.3389/fonc.2023.1142947

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