This study proposes a workflow integrating the aperture shape controller (ASC) in the Varian Eclipse system with a machine learning-based verification prediction model to improve gamma passing rates (GPRs) of LATTICE Radiotherapy (LRT) plans and redu...
This study aims to uncover the opaque decision-making process of an artificial intelligence (AI) agent for automatic treatment planning.We examined a previously developed AI agent based on the actor-critic with experience replay (ACER) network, which...
To develop and evaluate a deep reinforcement learning (RL) framework for rapid and automatic machine parameter optimization of volumetric modulated arc therapy (VMAT) treatment plans for localized prostate cancer.A multi-task policy network combining...
BACKGROUND: To investigate the feasibility and accuracy of PET radiomics features, along with their combination with CT radiomics, dosiomics, and deep learning (DL) features, in predicting radiation pneumonitis (RP) in lung cancer patients treated wi...
BACKGROUND AND PURPOSE: This study aims to develop a robust and user-friendly prediction model for radiation-induced hypothyroidism (RIHT) in nasopharyngeal carcinoma (NPC) patients.
. Gamma analysis serves as a critical safety assurance tool in radiotherapy, yet its broader clinical implementation remains constrained by insufficient error cause determination. To address this limitation, this study proposes a gamma passing rate (...
BACKGROUND: To evaluate the precision of automated segmentation facilitated by deep learning (DL) and dose calculation in adaptive radiotherapy (ART) for nasopharyngeal cancer (NPC), leveraging synthetic CT (sCT) images derived from cone-beam CT (CBC...
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 mode...
BACKGROUND: Proton therapy is commonly used for treating hepatocellular carcinoma (HCC); however, its feasibility can be challenging to assess in large tumors or those adjacent to critical organs at risk (OARs), which are typically assessed only afte...
Beam orientation optimization (BOO) in intensity-modulated radiation therapy (IMRT) is a complex, non-convex problem traditionally addressed with heuristic methods.This work demonstrates the potential improvement of the proposed BOO, providing a math...
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