解析延拓与不完全数据层析。

Journal of radiology and imaging Pub Date : 2021-03-01 Epub Date: 2021-03-04 DOI:10.14312/2399-8172.2021-2
Gengsheng L Zeng, Ya Li
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引用次数: 3

摘要

医学成像的一个独特特点是被成像的物体有一个紧凑的支撑。在数学中,一个有紧支持的函数的傅里叶变换是一个完整的函数。理论上,整个函数可以由它在一个小区域内的值唯一地确定,例如使用幂级数展开。幂级数展开式需要计算函数的所有阶导数,如果函数是离散采样的,这是不可能完成的任务。在本文中,我们提出了一种利用Nyquist-Shannon抽样定理对整个函数进行解析延拓的替代方法。所提出的方法涉及求解一个线性方程组,而不需要求函数的导数。给出了无噪声数据的计算机模拟。解析延拓是极端病态的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Analytic continuation and incomplete data tomography.

Analytic continuation and incomplete data tomography.

Analytic continuation and incomplete data tomography.

Analytic continuation and incomplete data tomography.

A unique feature of medical imaging is that the object to be imaged has a compact support. In mathematics, the Fourier transform of a function that has a compact support is an entire function. In theory, an entire function can be uniquely determined by its values in a small region, using, for example, power series expansions. Power series expansions require evaluation of all orders of derivatives of a function, which is an impossible task if the function is discretely sampled. In this paper, we propose an alternative method to perform analytic continuation of an entire function, by using the Nyquist-Shannon sampling theorem. The proposed method involves solving a system of linear equations and does not require evaluation of derivatives of the function. Noiseless data computer simulations are presented. Analytic continuation turns out to be extremely ill-conditioned.

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