Type
ThesisAuthors
Al-Awami, Ali K.
Advisors
Hadwiger, Markus
Committee members
Knox, ChristopherWonka, Peter

Program
Computer ScienceDate
2012-07Permanent link to this record
http://hdl.handle.net/10754/244615
Metadata
Show full item recordAbstract
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.Citation
Al-Awami, A. K. (2012). Large-Scale Context-Aware Volume Navigation using Dynamic Insets. KAUST Research Repository. https://doi.org/10.25781/KAUST-119USae974a485f413a2113503eed53cd6c53
10.25781/KAUST-119US