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A Real-Time Homography-Based Tracking Method for Tracking Deformable Tumor Motion in Fluoroscopy

机译:一种基于实时的诸如基于定位的透视荧光肿瘤运动的跟踪方法

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In radiation therapy, respiration-induced tumor motion significantly limits the efficiency of the radiation delivery, and brings potential risk to healthy organs and tissues. In order to deliver a sufficient high-dose radiation in adaptive with the tumor motion, a kilo-voltage (kV) X-ray fluoroscopy imaging system has been used to monitor the tumor motion in real-time during the treatment. In this paper, we present a fast and robust tracking algorithm to track deformable lung tumor motion in the kV fluoroscopic image sequence. Given a kV fluoroscopy, the tumor motion is represented by a non-linear homographic transformation of a pre-defined tumor template. The homographic transformation is then estimated by minimizing a sum-of-squared-difference (SSD) between the template image and the observed image. To improve the computational efficiency, an efficient second-order minimization method is employed to solve the problem of SSD minimization. The experimental results conducted on clinical kV fluoroscopies demonstrated that the proposed method is capable of tracking the tumor motion in real-time and its performance is superior to conventional tracking methods in terms of tracking accuracy and computational cost.
机译:在放射治疗中,呼吸诱导的肿瘤运动显着限制了辐射递送的效率,并为健康器官和组织带来了潜在风险。为了通过肿瘤运动提供足够的高剂量辐射,已经使用千伏电压(KV)X射线透视成像系统在治疗期间实时监测肿瘤运动。本文介绍了一种快速稳健的跟踪算法,可跟踪KV荧光透视图像序列中可变形的肺肿瘤运动。鉴于KV透视,肿瘤运动由预定义的肿瘤模板的非线性相同转化表示。然后通过最小化模板图像和观察图像之间的平方和平方和差异(SSD)来估计同类变换。为了提高计算效率,采用有效的二阶最小化方法来解决SSD最小化的问题。在临床KV荧光镜上进行的实验结果表明,该方法能够实时跟踪肿瘤运动,并且其性能优于跟踪精度和计算成本的传统跟踪方法。

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