广义模糊算子在DSA中的x线血管造影图像增强

Yuan Xinqi, Zhao Shujun, Zhou Fugen, Zhang Tao, Fu Weiwei, Xu Chuan, L. Min
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引用次数: 0

摘要

人们认为,模糊集理论是处理与模糊和/或不精确相关的不确定性的有用工具。本文利用模糊熵方法,提出了一种新的自适应图像模糊增强算法。在对模糊熵进行一般性讨论后,引入了模糊集的初等熵函数的概念。利用这种映射,在一定程度上有利于图像增强中阈值的选择。本文的第二部分研究了广义模糊算子的适用性,它不仅具有闭合性和自动调整性,而且具有对其他增强算法的移植性。最后以数字减影血管造影(Digital Subtraction Angiography, DSA)的x线血管造影图像为例对该算法进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
X-ray angiogram image enhancement in DSA with generalized fuzzy operator
It is believed that fuzzy set theory is a useful tool for handling the uncertainty associated with vagueness and/or imprecision. In this paper, by using a fuzzy entropy approach, a novel adaptive image fuzzy enhancement algorithm is presented. After a general discussion on fuzzy entropy, the concept of elementary entropy function of a fuzzy set is introduced. Using this mapping, the selection of the threshold value in image enhancement is beneficial to a certain extent. The second part of the paper investigates the applicability of the generalized fuzzy operator (GFO), which not only has a closing character and an automatic-adjusting character, but also has a transplant character to other enhancement arithmetic. One typical example is used for evaluation this algorithm at last, which is the X-ray angiogram image come from the Digital Subtraction Angiography (DSA).
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