A novel approach for cDNA image segmentation using SLIC based SOM methodology - Prasad Kondisetty, Durga; Ali Hussain, Mohammed (International Journal of Engineering and Technology, 2018)
In the segmentation of computer vision images, Super pixels are act as key role from last decade. There are multiple algorithms and techniques to analyze the Super pixels but amount all of them the best super pixel analyzing method is Simple Linear Iterative Clustering (SLIC) have come to pivot increasingly in recent years. The studying of micro array gene expression from MRI imaging is more useful to detect tumors or any other cancer diseases, so that the complementary DNA (cDNA) microarray is a well established tool for studying the same. The segmentation of microarray images is the main step in a microarray analysis. In this paper, we proposed an algorithm to segmenting the cDNA micro array image using Simple Linear Iterative Clustering (SLIC) based Self Organizing Maps (SOM) methodology. However, the proposed algorithm is taken up a challenging task to study the poor quality of images also. There are two steps to analyze the image, first, a pre-processing the applied image to reduce noise levels and second, to segment the image using SLIC based SOM methodology.