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Issue No.03 - May/June (2010 vol.30)
pp: 58-70
Won-Ki Jeong , Harvard University
Johanna Beyer , King Abdullah University of Science and Technology
Markus Hadwiger , King Abdullah University of Science and Technology
Rusty Blue , Kitware
Charles Law , Kitware
Amelio Vázquez-Reina , Tufts University
R. Clay Reid , Harvard Medical School
Jeff Lichtman , Harvard University
Hanspeter Pfister , Harvard University
ABSTRACT
Recent advances in optical and electron microscopy let scientists acquire extremely high-resolution images for neuroscience research. Data sets imaged with modern electron microscopes can range between tens of terabytes to about one petabyte. These large data sizes and the high complexity of the underlying neural structures make it very challenging to handle the data at reasonably interactive rates. To provide neuroscientists flexible, interactive tools, the authors introduce Ssecrett and NeuroTrace, two tools they designed for interactive exploration and analysis of large-scale optical- and electron-microscopy images to reconstruct complex neural circuits of the mammalian nervous system.
INDEX TERMS
neuroscience, connectome, segmentation, volume rendering, implicit surface rendering, graphics hardware, computer graphics, graphics and multimedia
CITATION
Won-Ki Jeong, Johanna Beyer, Markus Hadwiger, Rusty Blue, Charles Law, Amelio Vázquez-Reina, R. Clay Reid, Jeff Lichtman, Hanspeter Pfister, "Ssecrett and NeuroTrace: Interactive Visualization and Analysis Tools for Large-Scale Neuroscience Data Sets", IEEE Computer Graphics and Applications, vol.30, no. 3, pp. 58-70, May/June 2010, doi:10.1109/MCG.2010.56
REFERENCES
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2. W.-K. Jeong et al., "Scalable and Interactive Segmentation and Visualization of Neural Processes in EM Datasets," IEEE Trans. Visualization and Computer Graphics, vol. 15, no. 6, 2009, pp. 1505–1514.
3. A. Vázquez-Reina, E. Miller, and H. Pfister, "Multiphase Geometric Couplings for the Segmentation of Neural Processes," Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR 09), IEEE CS Press, 2009, pp. 2020–2027.
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