High-Fidelity Visualization of Large Medical Datasets on Commodity Hardware

Luigi Gallo, Alessio Pierluigi Placitelli
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引用次数: 3

Abstract

Recent advances in CT and MRI static and dynamic scanning techniques have led to great improvements in the resolution and size of volumetric medical datasets, and this trend is still ongoing. However, the explosion of dataset size prevents clinicians from taking advantage of an interactive, high-resolution exploration of volumetric medical data on commodity hardware, due to the memory constraints of modern graphics cards. This paper presents a hybrid CPU-GPU volume ray-casting method and some hybrid-based inspection tools aimed at providing interactive, medical-quality visualization using an ordinary desktop PC. Experimental results show that the hybrid method provides a near-interactive high-fidelity visualization of large medical datasets even if only limited hardware resources are available.
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商用硬件上大型医疗数据集的高保真可视化
CT和MRI静态和动态扫描技术的最新进展导致了体积医学数据集的分辨率和大小的巨大改进,并且这一趋势仍在继续。然而,由于现代显卡的内存限制,数据集大小的爆炸式增长阻碍了临床医生利用商品硬件上的交互式、高分辨率医学数据探索。本文提出了一种混合的CPU-GPU体积光线投射方法和一些基于混合的检测工具,旨在通过普通桌面PC提供交互式的、医疗质量的可视化。实验结果表明,即使硬件资源有限,该混合方法也能提供近交互的高保真大型医疗数据集可视化。
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