Automatic shadow enhancement in intra vascular ultrasound (IVUS) images

Maryam Basij, A. Taki, M. Yazdchi
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引用次数: 10

Abstract

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.
血管内超声(IVUS)图像的自动阴影增强
图像增强的目标是提高人类观众对图像信息的可解释性或感知能力。本文介绍了一种用于血管内超声(IVUS)图像中阴影区域检测和增强的自动算法,该算法使用自适应阈值法进行阈值选择,使用轮廓法进行边界检测,以及使用直方图分析进行阴影区域改进的图像增强算法。由于钙化斑块后面出现了阴影,这使得暗区很难或不可能在这些区域周围自动处理。在IVUS图像中,声影通常跟随硬斑块,它可以区分钙化区域和其他明亮区域。因此,我们提出用Otsu阈值分割钙化斑块,用无边缘的活动轮廓法分割图像的阴影区域,用直方图匹配增强图像的阴影。实验结果表明,该方法可以有效地检测复杂图像中的阴影区域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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