A bio-inspired CNN with re-indexing engine for lossless DNA microarray compression and segmentation

The DNA microarray images allow to analyze the natural gene expressions. In this paper we propose an advanced method to efficiently address the imaging storage as well as the performance of the algorithm used to retrieve information from DNA images. The cellular neural networks (CNNs) based core is able to provide a method to extract foreground (the DNA gene expression information) from DNA images. It is also proposed an innovative method to compress the DNA image by re-organizing the signal data belonging to the background by making use of a novel way to apply the re-indexing techniques to almost ¿uncorrelated¿ signal. Experiments confirm how the proposed method outperform previous solution in almost all cases.