Feasibility evaluation of novel AI‐based deep‐learning contouring algorithm for radiotherapy

PURPOSE: To evaluate the clinical feasibility of the Siemens Healthineers AI‐Rad Companion Organs RT VA30A (Organs‐RT) auto‐contouring algorithm for organs at risk (OARs) of the pelvis, thorax, and head and neck (H&N). METHODS: Computed tomography (CT) datasets from 30 patients (10 pelvis, 10 th...

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Detalles Bibliográficos
Autores principales: Maduro Bustos, Luis A., Sarkar, Abhirup, Doyle, Laura A., Andreou, Kelly, Noonan, Jodie, Nurbagandova, Diana, Shah, SunJay A., Irabor, Omoruyi Credit, Mourtada, Firas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Radiation Oncology Physics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10647981/
https://www.ncbi.nlm.nih.gov/pubmed/37464581
http://dx.doi.org/10.1002/acm2.14090

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10647981/
https://www.ncbi.nlm.nih.gov/pubmed/37464581
http://dx.doi.org/10.1002/acm2.14090

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