基于二维慢速医学成像模式的磁微体视觉跟踪多速率状态观测器

Mert Kaya, A. Denasi, S. Scheggi, Erdem Agbahca, ChangKyu Yoon, D. Gracias, S. Misra
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引用次数: 12

摘要

微创手术可以从微制剂中获益良多。为了保证手术的成功,这些微型药物需要清晰的可视化和精确的控制。由于医学成像模式的采集率低,因此可以使用多速率采样方法来估计微介质的样本间状态。因此,即使使用慢速医学成像方式获取位置数据,控制器的采样率也可以实际上增加。提出了用于微智能体视觉跟踪的多速率Luenberger和Kalman状态估计器。利用差分平方和和归一化互相关的视觉跟踪方法对微智能体进行跟踪。进一步,将两种方法的输出进行合并,使跟踪误差最小化,防止跟踪失败。在实验中,利用二维超声机和显微镜对不同几何形状和大小的微介质进行成像,并利用电磁线圈对其进行操纵。利用高速摄像机测量了多速率状态估计的精度。在具有挑战性的条件下,实验验证了跟踪和多速率状态估计的精度。为此,使用长度为48像素的椭圆形磁性微剂。对于8倍的采样率(每秒25帧),x和y轴的最大绝对误差分别为2.273和2.432像素。实验结果表明,基于归一化互相关的视觉跟踪可以更可靠地跟踪微agent,卡尔曼状态估计可以更准确地估计样本状态。实验结果表明,该方法可用于医学成像模式中微agent的跟踪和中间时刻系统状态的实时估计。
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A Multi-Rate State Observer for Visual Tracking of Magnetic Micro-Agents Using 2D Slow Medical Imaging Modalities
Minimally invasive surgery can benefit greatly from utilizing micro-agents. These miniaturized agents need to be clearly visualized and precisely controlled to ensure the success of the surgery. Since medical imaging modalities suffer from low acquisition rate, multi-rate sampling methods can be used to estimate the intersample states of micro-agents. Hence, the sampling rate of the controller can be virtually increased even if the position data is acquired using a slow medical imaging modality. This study presents multi-rate Luenberger and Kalman state estimators for visual tracking of micro-agents. The micro-agents are tracked using sum of squared differences and normalized cross correlation based visual tracking. Further, the outputs of the two methods are merged to minimize the tracking error and prevent tracking failures. During the experiments, the micro-agents with different geometrical shapes and sizes are imaged using a 2D ultrasound machine and a microscope, and manipulated using electromagnetic coils. The multi-rate state estimation accuracy is measured using a high speed camera. The precision of the tracking and multi-rate state estimation are verified experimentally under challenging conditions. For this purpose, an elliptical shaped magnetic micro-agent with a length of 48 pixels is used. Maximum absolute error in $x$ and $y$ axes are 2.273 and 2.432 pixels for an 8-fold increase of the sample rate (25 frames per second), respectively. During the experiments, it was observed that the micro-agents could be tracked more reliably using normalized cross correlation based visual tracking and inters ample states could be estimated more accurately using Kalman state estimator. Experimental results show that the proposed method could be used to track micro-agents in medical imaging modalities and estimate system states at intermediate time instants in real-time.
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