期刊
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
卷 15, 期 6, 页码 1505-1514出版社
IEEE COMPUTER SOC
DOI: 10.1109/TVCG.2009.178
关键词
Segmentation; neuroscience; connectome; volume rendering; implicit surface rendering; graphics hardware
资金
- Direct For Mathematical & Physical Scien
- Division Of Physics [0835713] Funding Source: National Science Foundation
- NCRR NIH HHS [P41-RR12553, P41 RR012553-10, P41 RR012553] Funding Source: Medline
- NIBIB NIH HHS [U54-EB005149, U54 EB005149, U54 EB005149-01] Funding Source: Medline
- NIGMS NIH HHS [P41 GM103545] Funding Source: Medline
Recent advances in scanning technology provide high resolution EM (Electron Microscopy) datasets that allow neuroscientists to reconstruct complex neural connections in a nervous system. However, due to the enormous size and complexity of the resulting data, segmentation and visualization of neural processes in EM data is usually a difficult and very time-consuming task. In this paper, we present NeuroTrace, a novel EM volume segmentation and visualization system that consists of two parts: a semi-automatic multiphase level set segmentation with 3D tracking for reconstruction of neural processes, and a specialized volume rendering approach for visualization of EM volumes. It employs view-dependent on-demand filtering and evaluation of a local histogram edge metric, as well as on-the-fly interpolation and ray-casting of implicit surfaces for segmented neural structures. Both methods are implemented on the GPU for interactive performance. NeuroTrace is designed to be scalable to large datasets and data-parallel hardware architectures. A comparison of NeuroTrace with a commonly used manual EM segmentation tool shows that our interactive workflow is faster and easier to use for the reconstruction of complex neural processes.
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