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Found 4 papers, 1 papers with code
ssEMnet: Serial-section Electron Microscopy Image Registration using a Spatial Transformer Network with Learned Features
The alignment of serial-section electron microscopy (ssEM) images is critical for efforts in neuroscience that seek to reconstruct neuronal circuits.
FusionNet: A deep fully residual convolutional neural network for image segmentation in connectomics
Electron microscopic connectomics is an ambitious research direction with the goal of studying comprehensive brain connectivity maps by using high-throughput, nano-scale microscopy.
Registering large volume serial-section electron microscopy image sets for neural circuit reconstruction using FFT signal whitening
The detailed reconstruction of neural anatomy for connectomics studies requires a combination of resolution and large three-dimensional data capture provided by serial section electron microscopy (ssEM).
Finding Mirror Symmetry via Registration
This new Mirror Symmetry via Registration (MSR) framework involves (1) data reflection with respect to an arbitrary plane, (2) registration of original and reflected datasets, and (3) calculation of the eigenvector of eigenvalue -1 for the transformation matrix representing the reflection and registration mappings.
