Reconstructing a connectome from an EM dataset often requires a large effort of proofreading automatically generated segmentations and synapses. There are two kinds of segmentation errors: false merges and false splits. To extract neuronal bodies from our datasets, proofreaders will interpret the ultrastructure in grayscale images by identify axons, dendrites and synapses in order to edit segmentation to correct falsely merged and over-segmented or falsely split neurons. NeuTu has a suite of tools to identify and correct both types of errors. NeuTu also provides intuitive functions for annotating synapses, including removing false positives, adding missing synapses and correcting synaptic connections.