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Extract-and-Match Geometric Corner and Step Pattern Approach for Registration of Fluoroscopic X-Ray Sequences

机译:荧光X射线序列注册的提取和匹配几何角和步进模式方法

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This paper presents a method to extract-and-match robust corner features based on connecting edges from the edge maps, mainly formed by coronary vascular junctions in fluoroscopic X-ray sequence images. Such images are challenging due to the aperture problem. To overcome this, existing approaches attempt to extract vessels for registration. However, they are ineffective in poor quality images. Our approach describes the extracted robust corner features in a rotation invariant manner using step patterns, followed by matching them effectively. Experimental results show that our approach performs very well (above 80%) in a dataset of poor quality fluoroscopic X-ray image sequences without extensive processing such as segmentation or learning.
机译:本文提出了一种基于从边缘图的连接边缘提取和匹配鲁棒角特征的方法,主要由荧光透视X射线序列图像中的冠状动脉血管结形成。由于孔径问题,这种图像是挑战。为了克服这一点,现有方法试图提取注册船只。然而,它们在劣质图像中无效。我们的方法描述了使用步骤模式以旋转不变的方式描述提取的鲁棒角特征,然后有效地匹配它们。实验结果表明,我们的方法在劣质荧光透视X射线图像序列的数据集中表现出非常好(高于80%),而无需广泛处理,例如分割或学习。

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