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Real time ultrasound image denoising using NVIDIA CUDA

机译:使用NVIDIA CUDA实时超声图像去噪

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摘要

Image filtering is a process of reducing noise which degrades the performance of image processing. In some applications such as segmentation or classification, denoising has been designed to smooth the homogeneous areas while keeping and enhancing the edges. In several applications such as video analysis, image-guided surgical interventions or visual servoing, real-time denoising is needed. The devoted filter was suggested to adjust the filter of anisotropic diffusion to the features of the multiplicative noise existing within the ultrasound video and also to make easier the filtering process. The purpose of this study is to decrease the processing time implementation of the diffusion function using parallel processors through the optimization of the Graphics processor unit (GPU). The results show that the suggested method is very effictive in terms of real-time compared to a standard central processing unit (CPU) implementation. Our proposed model magnifies the acceleration of the image filtering to 7X compared to the sequential calculation.
机译:图像滤波是减少噪声的过程,该噪声会降低图像处理的性能。在诸如分割或分类的一些应用中,已经设计了去噪以平滑均质区域,同时保持并增强边缘。在视频分析,图像引导的外科手术或视觉伺服等多种应用中,需要实时降噪。建议使用专用的滤波器来将各向异性扩散的滤波器调整为超声视频中存在的乘法噪声的特征,并使滤波过程更容易。这项研究的目的是通过优化图形处理器单元(GPU)来减少使用并行处理器的扩散函数的处理时间。结果表明,与标准中央处理器(CPU)实施相比,该方法在实时性方面非常有效。与顺序计算相比,我们提出的模型将图像过滤的加速度放大了7倍。

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