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Automatic detection, with confidence, of implanted radiographic seeds at megavoltage energies using an amorphous Silicon imager

机译:使用非晶硅成像仪自动检测在MegVoLTAGE能量下植入的放射线种子

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The premise of image guided radiotherapy is the use of imaging to target the delivery of radiotherapy with high precision. Despite the high resolution of amorphous silicon flat panel imagers the detection of small implanted radiographic gold markers (length: 5mm, diameter: 0.8mm), visualised on portal images with low SNR and the inherent low contrast of mega-voltage photons, remains a significant, safety critical challenge. Convolution/correlation and sum of the squares of the difference (SSD) detection algorithms make use of marker templates to detect radiographic markers. However, direct convolution is not specific enough and SSD techniques fail in low SNR conditions. This report defines a robust SSD measure operating on a model template-to-clinical convolution image and a semi-empirical template self-convolution image, which is used to assign an objective measure of confidence to individual markers and unambiguously determine the separation of true and false detection distributions. The algorithm was tested on 9 clinical pelvic images produced by placing a template with 14 randomly arranged gold markers on patients during portal imaging. Using 95% confidence limits in a localised regional search for each of the 14 seeds, the number of correct detections averaged at 13, while the average number of false detections was less than 1.
机译:图像引导放射疗法的前提是使用成像以高精度地靶向放射疗法。尽管无定形硅平板面板成像仪的高分辨率,但在具有低SNR的门户图像和Mega-电压光子的固有低对比度上,检测小型植入放射线金标记(长度:5mm,直径:0.8mm)的检测仍然是一个重要的,安全临界挑战。差异(SSD)检测算法的卷积/相关性和平方和使用标记模板来检测射线照相标记。但是,直接卷积不具体,并且SSD技术在低SNR条件下失败。此报告定义了在模型模板到临床卷积图像和半实证模板自卷积图像上运行的强大SSD测量,用于为个人标记分配客观衡量标记,并明确地确定真实的分离和实际情况假检测分布。在通过将模板放置在门网成像期间,通过将模板与14个随机排列的金色标记物置于患者的临床骨盆图像上进行了测试。在局部区域搜索中使用95%的置信范围,对14种种子中的每一个,平均在13处平均的正确检测数量,而误报的平均数量小于1。

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