Microarray Image Segmentation Based on Level Set and Regridding

As a significant technology, microarray technology plays an essential role in the life sciences research field. The processing of the microarray image is one of the critical phases of microarray technology. A suitable method provides accurate data for microarray technology and can increase experiment accuracy. Microarray image quality is typically poor due to uneven light, discoloration, temperature, artifacts, and instrument contamination. Segmenting the image becomes a challenging task. Irregular screening and level-setting methods are used to segment the microarray image in this article. First, we use an irregular grid method to divide the microarray image and ensure that each point is in a sub-image. Second, the level set method is used to segment the sub-images. Finally, we review the results and select the appropriate data as the final segmentation result. The result of the experiment shows that the proposed algorithm performs better than some related methods.