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实时纤维束成像:计算与可视化

Real-time tractography: computation and visualization.

作者信息

Chamberland Maxime, Yang Joseph Yuan-Mou, Aydogan Dogu Baran

机构信息

Department of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands.

Department of Neurosurgery, Neuroscience Advanced Clinical Imaging Service (NACIS), The Royal Children's Hospital, Melbourne, Australia.

出版信息

Brain Struct Funct. 2025 May 6;230(5):62. doi: 10.1007/s00429-025-02928-2.

Abstract

Did you know that even though tractography is often considered a computationally expensive and offline process, the latest algorithms can now be performed in real-time without sacrificing accuracy? Interactive real-time tractography has proven to be valuable in surgical planning and has the potential to enhance neuromodulation therapies, highlighting the importance of speed and precision in the generation of tractograms. This demand has driven the development of nearly 50 visualization tools over the past two decades, with advances in interactive real-time tractography offering new possibilities and providing rich insights into brain connectivity.

摘要

你知道吗?尽管纤维束成像通常被认为是一个计算成本高昂的离线过程,但最新的算法现在可以实时执行,而不牺牲准确性。交互式实时纤维束成像已被证明在手术规划中很有价值,并且有可能增强神经调节疗法,突出了在生成纤维束图时速度和精度的重要性。这种需求在过去二十年推动了近50种可视化工具的开发,交互式实时纤维束成像的进展提供了新的可能性,并为大脑连接性提供了丰富的见解。

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