Cellular Neural Networks, Navier-Stokes equation and microarray image reconstruction

Despite the latest improvements in the microarray technology, many developments are needed particularly in the image processing stage. Some hardware implementations of microarray image processing have been proposed and proved to be a promising alternative to the currently available software systems. However, the main drawback is the unsuitable addressing of the quantification of the gene spots which depend on many assumptions. It is our aim in this paper to present a new Image Reconstruction algorithm using Cellular Neural Network, which solves the Navier-Stokes equation. This algorithm offers a robust method to estimate the background signal within the gene spot region. Quantitative comparisons are carried out, between our approach and some available methods in terms of objective standpoint. It is shown that the proposed algorithm gives highly accurate and realistic measurements in a fully automated manner, and also, in a remarkably efficient time.