[A blood speckle reduction method based on temporal-spatial relativity of intravascular ultrasound].

College of Automation Engineering, Nanjing University of Aeronautics & Astronautics, Nanjing 210016, China.
Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi 01/2007; 23(6):1213-7.
Source: PubMed


The superior imaging manner of intravascular ultrasound becomes more and more widely used in the diagnosis of coronary heart disease and intervention therapy. However, as the frequency of ultrasound increases, strong speckled echo signal from blood may significantly decrease the contrast of lumen and arterial wall structure, which may make it difficult for doctor to diferentiate and measure geometrical parameters and physical parameters of lumen and plaque. In this paper a novel noise reduction method is introduced, which utilizes the temporal and spatial information of IUVS, that is blood echo speckles have higher temporal and spatial variation than the arterial wall. When signals transferred into the frequency field, tissue and blood present different frequency spectrum, then a radio of high frequency energy and low frequency energy is introduced to determine speckles or tissue. Result showed that the method can remarkably remove the speckle noise, increase the contrast and help doctor differentiate the arterial wall from the around tissues.

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    ABSTRACT: In order to overcome the blood-speckle noise and ambiguous boundary in intravascular ultrasound (IVUS) images, this paper proposes an algorithm for noise reduction and contrast enhancement based on the dyadic wavelet transform. In this algorithm, first, the noise variance is estimated according to the characteristics of IVUS images. Next, a method to calculate the local threshold is proposed based on the decomposed structure of dyadic wavelet transform. Then, the wavelet coefficients in different scales are treated using the shrinkage techniques which combine the soft threshold filtering with the hard one. Finally, a contrast enhancement algorithm is proposed based on the stretching of wavelet coefficient extreme and on the interpolating with Hermite polynomials. Experimental results indicate that, as compared with the existing denoising methods, the proposed algorithm is more practicable because it not only reduces the blood speckle noise but also enhances the image contrast without eliminating image details.
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