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Automatic shadow enhancement in intra vascular ultrasound (IVUS) images

机译:血管内超声(IVUS)图像中的自动阴影增强

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The goal of image enhancement is improving the interpretability or perception of information in images for human viewers. This paper describes, an automated algorithm for shadow region detection and enhancement in intravascular ultrasound (IVUS) images using an adaptive threshold method for threshold selection, contour approach for border detection and image enhancement algorithm including histogram analysis for the shadow regions improvement. As shadow appears behind the calcification plaque, it makes it difficult or impossible for the dark region to process automatically around these regions. The acoustic shadow usually follows the hard plaque in IVUS images and it can distinguish calcification regions from other bright regions. Therefore we propose to use Otsu Threshold for calcification plaque segmentation and the Active contours without edge method for shadow region separation of the image and histogram matching for shadow enhancing. Results show that the proposed method efficiently detected shadow regions even in complicated images.
机译:图像增强的目的是提高人类观看者对图像中信息的可解释性或感知性。本文介绍了一种自动算法,用于使用自适应阈值方法进行阈值选择的血管内超声(IVUS)图像中的阴影区域检测和增强,轮廓检测方法用于边界检测以及包括直方图分析的图像增强算法,用于改善阴影区域。由于阴影出现在钙化斑块后面,因此深色区域很难或不可能在这些区域周围自动处理。声影通常跟随IVUS图像中的硬斑块,并且可以将钙化区域与其他明亮区域区分开。因此,我们建议使用Otsu Threshold(大津阈值)进行钙化斑块分割,使用Active Edge无边线方法进行图像阴影区域分离,并使用直方图匹配进行阴影增强。结果表明,该方法即使在复杂图像中也能有效地检测阴影区域。

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