Scalable and interactive segmentation and visualization of neural processes in EM datasets

Recent advances in scanning technology provide high resolution EM (Electron Microscopy) datasets that allow neuro-scientists 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...

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Veröffentlicht in:IEEE transactions on visualization and computer graphics. - 1998. - 15(2009), 6 vom: 20. Nov., Seite 1505-14
1. Verfasser: Jeong, Won-Ki (VerfasserIn)
Weitere Verfasser: Beyer, Johanna, Hadwiger, Markus, Vazquez, Amelio, Pfister, Hanspeter, Whitaker, Ross T
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2009
Zugriff auf das übergeordnete Werk:IEEE transactions on visualization and computer graphics
Schlagworte:Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.
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520 |a Recent advances in scanning technology provide high resolution EM (Electron Microscopy) datasets that allow neuro-scientists 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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700 1 |a Hadwiger, Markus  |e verfasserin  |4 aut 
700 1 |a Vazquez, Amelio  |e verfasserin  |4 aut 
700 1 |a Pfister, Hanspeter  |e verfasserin  |4 aut 
700 1 |a Whitaker, Ross T  |e verfasserin  |4 aut 
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