Computer Methods and Programs in Biomedicine
Quantitative Improvements in cDNA Microarray Spot Segmentation
BSB '09 Proceedings of the 4th Brazilian Symposium on Bioinformatics: Advances in Bioinformatics and Computational Biology
Complementary DNA microarray image processing based on the fuzzy Gaussian mixture model
IEEE Transactions on Information Technology in Biomedicine - Special section on biomedical informatics
Segmentation of complementary DNA microarray images by wavelet-based Markov random field model
IEEE Transactions on Information Technology in Biomedicine - Special section on body sensor networks
A wavelet-based Markov random field segmentation model in segmenting microarray experiments
Computer Methods and Programs in Biomedicine
A novel neural network approach to cDNA microarray image segmentation
Computer Methods and Programs in Biomedicine
Regular gridding and segmentation for microarray images
Computers and Electrical Engineering
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Motivation: Although numerous algorithms have been developed for microarray segmentation, extensive comparisons between the algorithms have acquired far less attention. In this study, we evaluate the performance of nine microarray segmentation algorithms. Using both simulated and real microarray experiments, we overcome the challenges in performance evaluation, arising from the lack of ground-truth information. The usage of simulated experiments allows us to analyze the segmentation accuracy on a single pixel level as is commonly done in traditional image processing studies. With real experiments, we indirectly measure the segmentation performance, identify significant differences between the algorithms, and study the characteristics of the resulting gene expression data. Results: Overall, our results show clear differences between the algorithms. The results demonstrate how the segmentation performance depends on the image quality, which algorithms operate on significantly different performance levels, and how the selection of a segmentation algorithm affects the identification of differentially expressed genes. Availability: Supplementary results and the microarray images used in this study are available at the companion web site http://www.cs.tut.fi/sgn/csb/spotseg/ Contact: antti.lehmussola@tut.fi