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GPU-Based Visualization and Synchronization of 4-D Cardiac MR and Ultrasound Images

机译:基于GPU的4-D心脏MR和超声图像的可视化和同步

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In minimally invasive image-guided interventions, different imaging modalities, such as magnetic resonance imaging (MRI), computed tomography (CT), and 3-D ultrasound (US), can provide complementary, multispectral image information. Dynamic image registration is a well-established approach that permits real-time diagnostic information to be enhanced by placing lower-quality real-time images within a high quality anatomical context. For the guidance of cardiac interventions, it would be valuable to register dynamic MRI or CT with intra-operative US. However, in practice, either the high computational cost prohibits such real-time visualization, or else the resulting image quality is not satisfactory for accurate interventional guidance. Modern graphics processing units (GPUs) provide the programmability, parallelism and increased computational precision to address this problem. In this paper, we first outline our research on dynamic 3-D cardiac MR and US image acquisition, real-time dual-modality registration and US tracking. Next, we describe our contributions on image processing and optimization techniques for 4-D (3-D $+$ time) cardiac image rendering, and our GPU-accelerated methodologies for multimodality 4-D medical image visualization and optical blending, along with real-time synchronization of dual-modality dynamic cardiac images. Finally, multiple transfer functions, various image composition schemes, and an extended window-level setting and adjustment approach are proposed and applied to facilitate the dynamic volumetric MR and US cardiac data exploration and enhance the feature of interest of US image that is usually restricted to a narrow voxel intensity range.
机译:在微创图像引导的干预措施中,不同的成像方式,例如磁共振成像(MRI),计算机断层扫描(CT)和3-D超声(US),可以提供互补的多光谱图像信息。动态图像配准是一种公认​​的方法,通过将较低质量的实时图像放置在高质量的解剖环境中,可以增强实时诊断信息。对于心脏介入治疗的指导,在术中超声检查中进行动态MRI或CT登记将是很有价值的。但是,在实践中,要么高昂的计算成本就禁止了这种实时可视化,要么所得到的图像质量对于准确的介入指导并不令人满意。现代图形处理单元(GPU)提供了可编程性,并行性和更高的计算精度来解决此问题。在本文中,我们首先概述了对动态3-D心脏MR和US图像采集,实时双模式配准和US跟踪的研究。接下来,我们描述我们在4-D(3-D $ + $时间)心脏图像渲染的图像处理和优化技术上的贡献,以及用于多模态4-D医学图像可视化和光学融合的GPU加速方法,以及真实的模态动态心脏图像的时间同步。最后,提出并应用了多种传递函数,各种图像合成方案以及扩展的窗口级设置和调整方法,以促进动态容积MR和US心脏数据的探索,并增强了通常局限于狭窄的体素强度范围。

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