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A new medical image mosaic algorithm based on fuzzy sets recognition method

机译:基于模糊集识别方法的医学图像拼接新算法

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In the aspect of medical imaging, the large panoramic images can help doctors to conduct comprehensive and visual observation on the focus and the surrounding parts, so that image mosaicking has naturally become an issue which needs to be resolved intensively. This article proposed a new matching algorithm for image mosaic based on fuzzy sets recognition method to carry on regional characteristics matching combined medical imaging features. Taking perimeter, area, flat degrees, aspect ratio features as the regional characteristics, the right match point can be found with the use of fuzzy sets identification method, then a medical image mosaicking can be achieved by using eight parameter projective transformation principle and a gradual fade out of the method. On-the-spot experiments have proved that this algorithm is simple and easy to implement with strong robustness.
机译:在医学成像方面,大的全景图像可以帮助医生对焦点和周围部位进行全面的视觉观察,因此图像拼接自然成为一个亟待解决的问题。提出了一种基于模糊集识别方法的图像镶嵌匹配算法,对医学成像特征进行区域特征匹配。以周长,面积,平坦度,宽高比特征为区域特征,采用模糊集识别方法可以找到正确的匹配点,然后采用八参数投影变换原理和渐进的方法实现医学图像的镶嵌。淡出方法。现场实验证明,该算法简单易行,鲁棒性强。

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