Candidate Sampling for Neuron Reconstruction From Anisotropic Electron Microscopy Volumes

Candidate Sampling for Neuron Reconstruction From Anisotropic Electron Microscopy Volumes

Funke J, Martel JN, Gerhard S, Andres B, Cirecan DC, Giusti A, Gambardella LM, Schmidhuber J, Pfister H, Cardona A, and others.

(Springer: International Conference on Medical Image Computing and Computer-Assisted Intervention, 2014.)

The automatic reconstruction of neurons from stacks of electron microscopy sections is an important computer vision problem in neuroscience. Recent advances are based on a two step approach: First, a set of possible 2D neuron candidates is generated for each section independently based on membrane predictions of a local classifier. Second, the candidates of all sections of the stack are fed to a neuron tracker that selects and connects them in 3D to yield a reconstruction. The accuracy of the result is currently ...