Identifying the optimal deep learning architecture and parameters for automatic beam aperture definition in 3D radiotherapy

Purpose Two‐dimensional radiotherapy is often used to treat cervical cancer in low‐ and middle‐income countries, but treatment planning can be challenging and time‐consuming. Neural networks offer the potential to greatly decrease planning time through automation, but the impact of the wide range of...

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Bibliographic Details

Published in:	Journal of applied clinical medical physics Vol. 24; no. 12; pp. e14131 - n/a
Main Authors:	Gay, Skylar S., Kisling, Kelly D., Anderson, Brian M., Zhang, Lifei, Rhee, Dong Joo, Nguyen, Callistus, Netherton, Tucker, Yang, Jinzhong, Brock, Kristy, Jhingran, Anuja, Simonds, Hannah, Klopp, Ann, Beadle, Beth M., Court, Laurence E., Cardenas, Carlos E.
Format:	Journal Article
Language:	English
Published:	Malden Massachusetts John Wiley & Sons, Inc 01-12-2023
Subjects:	Architecture automatic segmentation Automation Cancer therapies Cervical cancer Deep learning digitally reconstructed radiograph Patients Planning Radiation therapy radiotherapy Standard scores Tomography
Online Access:	Get full text
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