Speeding up the Analysis of Neuron Morphology using Parallel Processing

Automated image analysis is used by pharmaceutical companies to measure changes in cell morphology, both rapidly and accurately. The field itself, dubbed High Content Analysis (HCA) is emerging as one of the fastest growing sectors in drug discovery and development. It represents the convergence between cell-based assays, high-resolution imaging, and advanced quantitative image analysis. There is no hard dividing line between High Content Screening (HCS) and HCA though the former is generally higher-throughput while the latter has an emphasis on gaining the maximum information from an assay, typically based on images. 

HCS systems achieve high throughput by rapidly capturing and processing data from entire micro-well plates. Each well in these plates contains cells or biochemical samples, which have been labeled to detect the changes induced by perturbations, such as addition of a candidate drug compound or a gene knockout. The images can be very dense, with hundreds of cells and complex cell morphology. It may take several hours or even days to process the images generated from a single experiment, which may be unacceptable in practice. The ideal image processing time lies within the same time frame as the image capturing.  Read more>>>>>>>>>>>>