Error Reduction on Automatic Segmentation in Microarray Image

DNA Microarray hybridization is a popular high throughput technique in academic as well as in industrial genomics research. The Microarray image is considered as an important tool and powerful technology for large-scale gene sequence and gene expression analysis. There are many methods to analyze the Microarray image by automatic segmentation or gridding spot. These methods always have the same problem of noise and tilt in spot array. It is difficult to process strong noise image in automation. In this paper, we can reduce the error of the edge detection which is influenced by noise and tilt spot array. We propose an automatic segmentation method with some techniques from video segmentation to process the Microarray image. By the proposed method, we can reduce the automatic spot segmentation errors and get more exact spot position. Our method has the advantages of low computation and easy implementation. Eventually, we compare the result with ScanAlyze tool since ScanAlyze tool extracts spot position and edge by artificial interface. We obtain the 1.43% average differential value of spots analysis ratio in result with ScanAlyze.