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首页> 外文期刊>International Journal of Engineering Research and Applications >A Novel Approach for Medical Image Stitching Using Ant Colony
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A Novel Approach for Medical Image Stitching Using Ant Colony

机译:一种利用蚁群进行医学图像拼接的新方法

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Image stitching is one of important technologies in medical image processing field. In digital radiography oversized images have to be assembled from multiple exposures as the flat panel of an X-ray system cannot cover all part of a body. The stitching of X-ray images is carried out by employing two basic steps: Registration and Blending. The classical registration methods such as SIFT and SURF search for all the pixels to get the best registration. These methods are slow and cannot perform well for high resolution X-ray images. Therefore a fast and accurate feature based technique using ant colony optimization is implemented in the present work. This technique not only saves time but also gives the accuracy to stitch the image. This technique is also used for finding the edges for land marking and features of different X-ray images. Correlation is found between landmarks to check the alignment between the images and RANSAC algorithm is used to eliminate the spurious feature points. Finally alpha- blending technique is used to stitch the images.
机译:图像拼接是医学图像处理领域的重要技术之一。在数字射线照相中,由于X射线系统的平板无法覆盖人体的所有部分,因此必须通过多次曝光来组合超大尺寸的图像。 X射线图像的缝合是通过两个基本步骤完成的:套准和混合。 SIFT和SURF等经典配准方法会搜索所有像素以获得最佳配准。这些方法很慢,无法对高分辨率X射线图像执行良好。因此,在当前工作中实现了使用蚁群优化的基于快速和准确特征的技术。此技术不仅可以节省时间,而且可以提供缝合图像的准确性。该技术还用于查找边缘标记的边缘和不同X射线图像的特征。在地标之间找到相关性,以检查图像之间的对齐方式,并使用RANSAC算法消除虚假特征点。最后,使用alpha混合技术缝制图像。

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