dive

A deep neural network model architecture that is highly optimized for serial-section transmitted electron microscopy image segmentation. We trained a pixel classifier that operates on raw pixel intensities with no preprocessing to generate probability values for each pixel being a membrane or not. While the use of neural networks in image segmentation is not completely new, we developed novel insights and model architectures that allow us to achieve superior performance on EM image segmentation tasks. Our submission based on these insights to the 2D EM Image Segmentation Challenge achieved the best performance consistently across all the three evaluation metrics.