Despite this understanding, the absence of a standardised protocol has limited the use of differentiated SH-SY5Y cells in high-throughput assay formats. Differentiation of the SH-SY5Y cells is a necessary step to obtain cells that express mature neuronal markers. SH-SY5Y cells have been widely used as a neuronal model, yet commonly in an undifferentiated state that is not representative of mature neurons. Adapting these models to a high-throughput format enables simultaneous screening of multiple agents within a single assay. Neuronal models are a crucial tool in neuroscientific research, helping to elucidate the molecular and cellular processes involved in disorders of the nervous system. The presented methods achieve homogenously distributed differentiated SH-SY5Y cells, useful for researchers using these cells in high-throughput screening assays. We then demonstrated the efficacy of our techniques by optimising it further for neurite outgrowth analysis. Room temperature pre-incubation for 1 h improved the plating homogeneity within the well and the ability to analyse neurites. SH-SY5Y cells seeded at an initial density of 2,500 cells/well in a 96-well plate provide sufficient space for neurites to extend, without impacting cell viability. Here, we describe techniques to differentiate and re-plate SH-SY5Y cells within a 96-well plate for high-throughput screening. © 2013 International Society for Advancement of Cytometry. The proposed method will help determining the effects of compounds on cultures with dense neurite networks, thereby boosting physiological relevance of cell-based assays in the context of neuronal diseases. Quantitative comparison showed a superior performance of MorphoNeuroNet to existing analysis tools, especially for revealing subtle changes in thin neurites, which have weak fluorescence intensity compared to the rest of the network. The image analysis pipeline consists of a multi-tier approach in which the somas are segmented by adaptive region growing using nuclei as seeds, and the neurites are delineated by a combination of various intensity and edge detection algorithms. MorphoNeuroNet, written as a script for ImageJ, Java based freeware, automatically determines various morphological parameters of the soma and the neurites (size, shape, starting points, and fractional occupation). Here, we present a fully automated method for quantifying the morphology of neurons and the density of neurite networks, in dense neuronal cultures, which are grown for more than 10 days. However, most existing methods show poor performance for well-connected and differentiated neuronal networks, which may serve as valuable models for inter alia synaptogenesis. To analyze neuronal morphology, automatic image analysis pipelines have been conceived, which accurately quantify the shape changes of neurons in cell cultures with non-dense neurite networks. High content cell-based screens are rapidly gaining popularity in the context of neuronal regeneration studies.