Combining autoencoder with clustering analysis for anomaly detection in radiotherapy plans

BACKGROUND: To develop an unsupervised anomaly detection method to identify suspicious error-prone treatment plans in radiotherapy. METHODS: A total of 577 treatment plans of breast cancer patients were used in this study. They were labeled as either normal or abnormal plans by experienced clinician...

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Detalles Bibliográficos
Autores principales: Huang, Peng, Yan, Hui, Song, Zhiyue, Xu, Yingjie, Hu, Zhihui, Dai, Jianrong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2023
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10102771/
https://www.ncbi.nlm.nih.gov/pubmed/37064364
http://dx.doi.org/10.21037/qims-22-825

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10102771/
https://www.ncbi.nlm.nih.gov/pubmed/37064364
http://dx.doi.org/10.21037/qims-22-825

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