Microarray images consist of thousands of spots, each of which corresponds to a different biological material. The microarray segmentation problem is to work out which pixels belong to which spots, even in presence of noise and corruption. We propose a solution based on deep neural networks, which achieves excellent results both on simulated and experimental data. We have made the source code for our solution available on Github under a permissive license.
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