Katouzian Amin author Columbia University. Biomedical Engineering Angelini Elsa D. author Lorsakul Auranuch author Columbia University. Biomedical Engineering Sturm Bernhard author Laine Andrew F. author Columbia University. Biomedical Engineering Columbia University. Radiology Columbia University. Biomedical Engineering originator text Articles 2009 English In this paper, intravascular ultrasound (IVUS) grayscale images, acquired with a single-element mechanically rotating transducer, are processed with wavelet denoising and region-based segmentation to extract various layers of lumen contours and plaques. First, IVUS volumetric data is expanded on complex exponential wavelet-like basis functions, also known as Brushlets, which are well localized in time and frequency domains. Brushlets denoising have demonstrated in the past a great aptitude for denoising ultrasound data and removal of blood speckles. A region-based segmentation framework is then applied for detection of lumen border layers, which remains one of the most challenging problems in IVUS image analysis for images acquired with a single element, mechanically rotating 45 MHz transducer. We evaluated hard thresholding for Brushlet denoising, and compared segmentation results to manually traced lumen borders. We observed good agreement and suggest that the proposed algorithm has a great potential to be used as a reliable pre-processing step for accurate lumen border detection. Functional imaging and modeling of the heart : 5th international conference, FIMH 2009, Nice, France, June 3-5, 2009 : proceedings, Lecture Notes in Computer Science, Volume 5528 (Berlin ; New York : Springer, 2009), pp. 104-113. Biomedical engineering http://dx.doi.org/10.1007/978-3-642-01932-6_12 http://hdl.handle.net/10022/AC:P:9520 NNC NNC 2010-08-23 16:41:12 -0400 2012-07-27 11:49:20 -0400 2118 eng