Deep Neural Networks Segment Neuronal Membranes in Electron Microscopy Images
University of Applied Sciences and Arts of Southern Switzerland · Dalle Molle Institute for Artificial Intelligence Research
Abstract
We address a central problem of neuroanatomy, namely, the automatic segmentation of neuronal structures depicted in stacks of electron microscopy (EM) images. This is necessary to efficiently map 3D brain structure and connectivity. To segment biological neuron membranes, we use a special type of deep artificial neural network as a pixel classifier. The label of each pixel (membrane or non-membrane) is predicted from raw pixel values in a square window centered on it. The input layer maps each window pixel to a neuron. It is followed by a succession of convolutional and max-pooling layers which preserve 2D information and extract features with increasing levels of abstraction. The output layer produces a…
Citation impact
- FWCI
- 103.67
- Percentile
- 100%
- References
- 28
Authors
4- DCDan CireşanCorresponding
University of Applied Sciences and Arts of Southern Switzerland, Dalle Molle Institute for Artificial Intelligence Research
- AGAlessandro Giusti
University of Applied Sciences and Arts of Southern Switzerland, Dalle Molle Institute for Artificial Intelligence Research
- LMLuca Maria Gambardella
University of Applied Sciences and Arts of Southern Switzerland, Dalle Molle Institute for Artificial Intelligence Research
- JSJürgen Schmidhuber
University of Applied Sciences and Arts of Southern Switzerland, Dalle Molle Institute for Artificial Intelligence Research
Topics & keywords
- Pixel
- Artificial intelligence
- Computer science
- Pattern recognition (psychology)
- Ground truth
- Segmentation
- Convolutional neural network
- Perceptron