A Fully Automatic Method for Gridding Bright Field Images of Bead-Based Microarrays

作者：Datta Abhik^*; Kong Adams Wai Kin^*; Yow Kin Choong^*

来源：IEEE Journal of Biomedical and Health Informatics, 2016, 20(4): 1148-1159.

DOI：10.1109/JBHI.2015.2436928

• Bead microarray
• gridding
• iterative closest point
• mean shift
• RANSAC

In this paper, a fully automatic method for gridding bright field images of bead-based microarrays is proposed. There have been numerous techniques developed for gridding fluorescence images of traditional spotted microarrays but to our best knowledge, no algorithm has yet been developed for gridding bright field images of bead-based microarrays. The proposed gridding method is designed for automatic quality control during fabrication and assembly of bead-based microarrays. The method begins by estimating the grid parameters using an evolutionary algorithm. This is followed by a grid-fitting step that rigidly aligns an ideal grid with the image. Finally, a grid refinement step deforms the ideal grid to better fit the image. The grid fitting and refinement are performed locally and the final grid is a nonlinear (piecewise affine) grid. To deal with extreme corruptions in the image, the initial grid parameter estimation and grid-fitting steps employ robust search techniques. The proposed method does not have any free parameters that need tuning. The method is capable of identifying the grid structure even in the presence of extreme amounts of artifacts and distortions. Evaluation results on a variety of images are presented.

• 出版日期2016-7