带符号距离函数的大规模数字重建脑电路的高保真可视化

2019 IEEE Visualization Conference (VIS) Pub Date : 2019-10-01 DOI:10.1109/VISUAL.2019.8933693

Jonas Karlsson, M. Abdellah, Sébastien Speierer, A. Foni, Samuel Lapere, F. Schürmann

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引用次数: 2

摘要

我们探索了第一个概念验证应用程序，用于使用符号距离函数可视化大规模数字重建的脑电路。与使用隐式几何相比，我们的方法的重要性得到了证明，隐式几何只能提供神经元的自然外观，而显式几何则需要大量的内存，并且在更大的电路中具有有限的可扩展性。

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High Fidelity Visualization of Large Scale Digitally Reconstructed Brain Circuitry with Signed Distance Functions

We explore a first proof-of-concept application for visualizing large scale digitally reconstructed brain circuitry using signed distance functions. The significance of our method is demonstrated in comparison with using implicit geometry that is limited to provide the natural look of neurons or explicit geometry that requires huge amounts of memory and has limited scalability with larger circuits.

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2019 IEEE Visualization Conference (VIS)

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