Criteria-calibration approaches to deep learning-based cervical cancer radiation treatment auto-planning

Criteria-calibration approaches to deep learning-based cervical cancer radiation treatment auto-planning

Abstract Background Knowledge-Based Planning (KBP) pipelines, which integrate machine learning-based models to predict dose distribution, have gained popularity in clinical radiation therapy. However, for patients with specific requirements, the trained models may struggle to rapidly adjust to guide...

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Bibliographic Details
Main Authors: Yongguang Liang, Jingru Yang, Shuoyang Wei, Yanfei Liu, Shumeng He, Kang Zhang, Jie Qiu, Bo Yang
Format: Article
Language:English
Published: BMC 2025-08-01
Series:Radiation Oncology
Subjects:
Knowledge-based planning
Auto-planning
uTPS
Prediction tolerance
Online Access:https://doi.org/10.1186/s13014-025-02684-x
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https://doi.org/10.1186/s13014-025-02684-x

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