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A real-time homography-based tracking method for tracking deformable tumor motion in fluoroscopy

机译:一种基于单应性成像的实时荧光跟踪方法

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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 nonlinear 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,呼吸引起的肿瘤运动显着限制了放射传递的效率,并给健康的器官和组织带来了潜在的风险。为了提供足够的高剂量辐射以适应肿瘤运动,在治疗过程中已经使用了千伏(kV)X射线荧光透视成像系统来实时监测肿瘤运动。在本文中,我们提出了一种快速且鲁棒的跟踪算法,以跟踪kV荧光镜图像序列中可变形的肺肿瘤运动。给定kV荧光检查,肿瘤运动由预先定义的肿瘤模板的非线性单应变换表示。然后通过最小化模板图像和观察图像之间的平方差和(SSD)来估计同构变换。为了提高计算效率,采用了一种有效的二阶最小化方法来解决SSD最小化的问题。对临床kV荧光检查进行的实验结果表明,该方法能够实时跟踪肿瘤运动,并且在跟踪精度和计算成本方面均优于常规跟踪方法。

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