Latest developments in electron microscopy (EM) technology produce high resolution images that enable neuro-scientists to identify and put together the complex
neural connections in a nervous system. However, because of the massive size and
underlying complexity of this kind of data, processing, navigation and analysis suffer
drastically in terms of time and effort. In this work, we propose the use of state-of-
the-art navigation techniques, such as dynamic insets, built on a peta-scale volume visualization framework to provide focus and context-awareness to help neuro-scientists
in their mission to analyze, reconstruct, navigate and explore EM neuroscience data.
| Date of Award | Jul 2012 |
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| Original language | English (US) |
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| Awarding Institution | - Computer, Electrical and Mathematical Sciences and Engineering
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| Supervisor | Markus Hadwiger (Supervisor) |
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