Intravascular ultrasound( IVUS) is an important imaging technique that is used to study vascular wall architecture for diagnosis and assessment of the vascular diseases. Segmentation of lumen and media-adventitia boun...Intravascular ultrasound( IVUS) is an important imaging technique that is used to study vascular wall architecture for diagnosis and assessment of the vascular diseases. Segmentation of lumen and media-adventitia boundaries from IVUS images is a basic and necessary step for quantitative assessment of the vascular walls.Due to ultrasound speckles, artifacts and individual differences,automated segmentation of IVUS images represents a challenging task. In this paper,a random walk based method is proposed for fully automated segmentation of IVUS images. Robust and accurate determination of the seed points for different regions is the key to successful use of the random walk algorithm in segmentation of IVUS images and is the focus of the present work. Performance of the proposed algorithm was evaluated over an image database with 900 IVUS image frames of nine patient cases. The preliminary experimental results show the potential of the proposed IVUS image segmentation approach.展开更多
基金Innovation Program of Shanghai Municipal Education Commission,China(No.13YZ136)National Science&Technology Support Program during the 12th Five-Year Plan Period of China(No.2012BAI13B02)
文摘Intravascular ultrasound( IVUS) is an important imaging technique that is used to study vascular wall architecture for diagnosis and assessment of the vascular diseases. Segmentation of lumen and media-adventitia boundaries from IVUS images is a basic and necessary step for quantitative assessment of the vascular walls.Due to ultrasound speckles, artifacts and individual differences,automated segmentation of IVUS images represents a challenging task. In this paper,a random walk based method is proposed for fully automated segmentation of IVUS images. Robust and accurate determination of the seed points for different regions is the key to successful use of the random walk algorithm in segmentation of IVUS images and is the focus of the present work. Performance of the proposed algorithm was evaluated over an image database with 900 IVUS image frames of nine patient cases. The preliminary experimental results show the potential of the proposed IVUS image segmentation approach.
