微陣列技術利用雜合(Hybridization)反應偵測RNA在樣本中的基因表現量，微陣列影像資料分析對推估基因表現量是非常重要的一個步驟。不同影像資料分析方法所得之結果，將會嚴重影響後續的統計分析和結論。在此研究中，我們利用二維度K-means切割微陣列影像，並且移除干擾因子以得到更準確的估計量。最後我們和混合模型切割方法比較replicates之間的相關係數和變異數，可以得知我們整體上有較高的相關係數，並且在整個影像強度上有較一致的變異程度。

DNA microarray experiment is a high throughout technology to assay gene expression level that is proportional to the intensities. Accurate image analysis is important to explore differential expressed genes. Different image analysis will influent statistical conclusion. In our study, we segment image by two-dimensional K-means with removal of unreliable pixels to obtain more accurate estimates. We compare our results with those obtained by mixture model. Our method results in higher correlation and consistent variance across replicates.

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