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CVPR
2010
IEEE

Increasing depth resolution of Electron Microscopy of Neural circuits using Sparse Tomographic reconstruction

11 years 9 months ago
Increasing depth resolution of Electron Microscopy of Neural circuits using Sparse Tomographic reconstruction
Future progress in neuroscience hinges on reconstruction of neuronal circuits to the level of individual synapses. Because of the specifics of neuronal architecture, imaging must be done with very high resolution and throughput. While Electron Microscopy (EM) achieves the required resolution in the transverse directions, its depth resolution is a severe limitation. Computed tomography (CT) may be used in conjunction with electron microscopy to improve the depth resolution, but this severely limits the throughput since several tens or hundreds of EM images need to be acquired. Here, we exploit recent advances in signal processing to obtain high depth resolution EM images computationally. First, we show that the brain tissue can be represented as sparse linear combination of local basis functions that are thin membrane-like structures oriented in various directions. We then develop reconstruction techniques inspired by compressive sensing that can reconstruct the brain tissue from very ...
Ashok Veeraraghavan, Alex Genkin, Shiv Vitaladevun
Added 31 Mar 2010
Updated 14 May 2010
Type Conference
Year 2010
Where CVPR
Authors Ashok Veeraraghavan, Alex Genkin, Shiv Vitaladevuni, Lou Scheffer, Shan Xu, Harald Hess, Graham Knott, Dmitri Chklovskii
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