BACKGROUND: Radiotherapy treatment planning traditionally involves complex and time-consuming processes, often relying on trial-and-error methods. The emergence of artificial intelligence, particularly Large Language Models (LLMs), surpassing human c...
To better integrate into processes like rapid adaptive planning and quality assurance, this study aims to propose a lightweight and universal proton spot dose calculation model suitable for arbitrary energies.Given the alignment between the character...
INTRODUCTION: Nasopharyngeal carcinoma (NPC) typically presents as advanced disease due to the lack of significant symptoms in the early stages. Accurate prognostication is therefore challenging as current methods based on anatomical staging often la...
OBJECTIVES: To audit prospectively the accuracy, time saving, and utility of a commercial artificial intelligence auto-contouring tool (AIAC). To assess the reallocation of time released by AIAC.
BACKGROUND: Palliative spine radiation therapy is prone to treatment at the wrong anatomic level. We developed a fully automated deep learning-based spine-targeting quality assurance system (DL-SpiQA) for detecting treatment at the wrong anatomic lev...
PURPOSE: Most research on artificial intelligence-based auto-contouring as template (AI-assisted contouring) for organs-at-risk (OARs) stem from high-income countries. The effect and safety are, however, likely to depend on local factors. This study ...
Machine- and patient-specific quality assurance (QA) is essential to ensure the safety and accuracy of radiotherapy. QA methods have become complex, especially in high-precision radiotherapy such as intensity-modulated radiation therapy (IMRT) and vo...
OBJECTIVES: To determine if Limbus, an artificial intelligence (AI) auto-contouring software, can offer meaningful time savings for prostate radiotherapy treatment planning.
Technology in cancer research & treatment
Jan 1, 2024
Intensity-modulated radiotherapy (IMRT) is currently the most important treatment method for nasopharyngeal carcinoma (NPC). This study aimed to enhance prediction accuracy by incorporating dose information into a deep convolutional neural network (...
Technology in cancer research & treatment
Jan 1, 2024
Deep learning (DL) is widely used in dose prediction for radiation oncology, multiple DL techniques comparison is often lacking in the literature. To compare the performance of 4 state-of-the-art DL models in predicting the voxel-level dose distribu...
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