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An 'Optimal' k-Needle Placement Strategy Given an Approximate Initial Needle Position

机译:给定近似初始针位置的“最佳”k针置策略

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In this paper we address the problem of finding an "optimal" strategy for placing k biopsy needles, given a large number of possible initial needle positions. THis problem arises for example in guided, endoscopic needle biopsies, where the position of the endoscope's tip is known with some error. We consider tow variations of the problem: (1) Calculate the smallest set of needles, needed to guarantee a successful biopsy. (2) Given a number k, calculate k needles such that the probability of a successful biopsy is maximized. We formulate both problems in terms of two general, NP-hard optimization problems. Our solution to both problems is "optimal" with respect to the best approximative algorithm known for the respective NP-hard problem. For the latter problem there exists an approximative algorithm which requires virtually no implementation effort and is guaranteed to be within a factor of 1-1/e of the exact solution. For both variations of the problem we are able to provide success probabilities for each needle to the physician. We have implemented the approximative algorith, for the second variation. The resulting probabilities show that our approach can provide valuable decision support for the physician in choosing how many needles to place an how to place them.
机译:在本文中,考虑到大量可能的初始针位置,我们解决了寻找k活检针的“最佳”策略的问题。该问题例如在引导的内窥镜针活检中出现,其中内窥镜尖端的位置具有一些误差。我们考虑牵引问题的变化:(1)计算确保成功的活检所需的最小针套。 (2)给定k,计算K针,使得成功活组织检查的概率最大化。我们在两个普通的NP-Hard优化问题方面制定了两个问题。我们对两个问题的解决方案是关于相应NP难题所知的最佳近似算法的“最佳”。对于后一种问题,存在一种近似算法,其几乎不需要实现工作,并且保证在精确解决方案的1-1 / e的因子范围内。对于问题的两种变化,我们能够为医生提供每个针头的成功概率。我们已经实现了近似的算法,用于第二种变化。由此产生的概率表明,我们的方法可以为医生提供有价值的决策支持,在选择有多少针来放置如何放置它们时。

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