Deep learning-augmented radioluminescence imaging for radiotherapy dose verification.
Deep learning-augmented radioluminescence imaging for radiotherapy dose verification.
复制标题
用于放射治疗剂量验证的深度学习增强放射发光成像。
DOI：
10.1002/mp.15229
复制
发表时间：
2021
期刊：
影响因子：
3.8
通讯作者：
Wang,Lei
中科院分区：
文献类型：
--
作者：
Jia,Mengyu;Yang,Yong;Wu,Yan;Li,Xiaomeng;Xing,Lei;Wang,Lei
PurposeWe开发了一种新的剂量验证方法，使用基于相机的放射性发光成像系统（CRIS）结合基于深度学习的信号处理technique. MethodsCRIS由一个圆柱形腔室组成，该圆柱形腔室的内表面涂有闪烁体材料，两端连接有半球形反射镜和数码相机。训练后，深度学习模型用于图像到剂量转换，以在TPS设置和实际射束能量之间具有良好一致性的假设下，从单个CRIS图像提供特定水体模多个深度处的绝对剂量预测。为了收集可接受的数据，使用一组捕获的放射发光图像和来自临床治疗计划系统（TPS）的相应剂量图对模型进行训练。为了克服TPS计算和相应测量之间存在的潜在误差和不一致性，该模型以无监督的方式进行训练。对5个方形野（范围从2 × 2到10 × 10 cm 2）和3个临床调强放射治疗（IMRT）病例进行了验证实验。结果进行了比较，TPS计算的伽马指数在1.5，5，和10 cm depths.ResultsThe平均2%/2 mm伽马通过率为100%，为方形字段和97.2%（范围从95.5%到99.5%）的IMRT字段。通过将CRIS结果与各种常规视野的测量结果进行比较，进行了进一步验证。结果表明，平均伽马通过率为91%（1%/1 mm）的交叉配置文件和平均百分比偏差为1.15%的百分比深度剂量（PDDs）。结论该系统能够将辐照的放射性发光图像转换为相应的水基剂量图在多个深度的空间分辨率相媲美的TPS计算。
PurposeWe developed a novel dose verification method using a camera‐based radioluminescence imaging system (CRIS) combined with a deep learning‐based signal processing technique.MethodsThe CRIS consists of a cylindrical chamber coated with scintillator material on the inner surface of the cylinder, coupled with a hemispherical mirror and a digital camera at the two ends. After training, the deep learning model is used for image‐to‐dose conversion to provide absolute dose prediction at multiple depths of a specific water phantom from a single CRIS image under the assumption of a good consistency between the TPS setting and actual beam energy. The model was trained using a set of captured radioluminescence images and the corresponding dose maps from the clinical treatment planning system (TPS) for the sake of acceptable data collection. To overcome the latent error and inconsistency that exists between the TPS calculation and the corresponding measurement, the model was trained in an unsupervised manner. Validation experiments were performed on five square fields (ranging from 2 × 2 to 10 × 10 cm2) and three clinical intensity‐modulated radiation therapy (IMRT) cases. The results were compared to the TPS calculations in terms of gamma index at 1.5, 5, and 10 cm depths.ResultsThe mean 2%/2 mm gamma pass rates were 100% for square fields and 97.2% (range from 95.5% to 99.5%) for the IMRT fields. Further validations were performed by comparing the CRIS results with measurements on various regular fields. The results show a mean gamma pass rate of 91% (1%/1 mm) for cross‐profiles and a mean percentage deviation of 1.15% for percentage depth doses (PDDs).ConclusionsThe system is capable of converting the irradiated radioluminescence image to corresponding water‐based dose maps at multiple depths with a spatial resolution comparable to the TPS calculations.
用于基于荧光屏的几何 QA 系统 (RavenQA™) 的单光学内核，作为患者特定 IMRT/VMAT QA 的工具
影响因子：
3.5
作者：
Minsik Lee;K. Ding;B. Yi
通讯作者：
B. Yi
影响因子：
3.8
作者：
Frelin, A-M.;Fontbonne, J-M.;Leroux, T.
通讯作者：
Leroux, T.