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Real-time optical properties and oxygenation imaging using custom parallel processing in the spatial frequency domain

机译:使用自定义并行处理在空间频域中进行实时光学特性和氧合成像

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摘要

The development of real-time, wide-field and quantitative diffuse optical imaging methods is becoming increasingly popular for biological and medical applications. Recent developments introduced a novel approach for real-time multispectral acquisition in the spatial frequency domain using spatio-temporal modulation of light. Using this method, optical properties maps (absorption and reduced scattering) could be obtained for two wavelengths (665 nm and 860 nm). These maps, in turn, are used to deduce oxygen saturation levels in tissues. However, while the acquisition was performed in real-time, processing was performed post-acquisition and was not in real-time. In the present article, we present CPU and GPU processing implementations for this method with special emphasis on processing time. The obtained results show that the proposed custom direct method using a General Purpose Graphic Processing Unit (GPGPU) and C CUDA (Compute Unified Device Architecture) implementation enables 1.6 milliseconds processing time for a 1 Mega-pixel image with a maximum average error of 0.1% in extracting optical properties.
机译:对于生物和医学应用,实时,宽视场和定量漫射光学成像方法的开发正变得越来越流行。最近的发展引入了一种新颖的方法,该方法使用光的时空调制在空间频域中进行实时多光谱采集。使用此方法,可以获得两个波长(665 nm和860 nm)的光学特性图(吸收和减少的散射)。这些图又用于推断组织中的氧饱和度水平。但是,虽然实时进行采集,但是处理是在采集后进行的,而不是实时进行的。在本文中,我们介绍此方法的CPU和GPU处理实现,并特别强调处理时间。获得的结果表明,使用通用图形处理单元(GPGPU)和C CUDA(计算机统一设备体系结构)实现的建议的自定义直接方法能够为1兆像素的图像提供1.6毫秒的处理时间,最大平均误差为0.1%在提取光学特性方面。

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