Automatic Shadow Enhancement in Intra Vascular Ultrasound (IVUS) Images

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 plague, 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 plague 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.