An improved K-means clustering method for cDNA microarray image segmentation
| العنوان: | An improved K-means clustering method for cDNA microarray image segmentation |
|---|---|
| المؤلفون: | Shunxiang Wu, Wang Tn, Tiejun Li, Gui-Fang Shao |
| المصدر: | Genetics and Molecular Research. 14:7771-7781 |
| بيانات النشر: | Genetics and Molecular Research, 2015. |
| سنة النشر: | 2015 |
| مصطلحات موضوعية: | business.industry, Computer science, k-means clustering, Pattern recognition, General Medicine, Image segmentation, Expression (mathematics), Image (mathematics), Gene Expression Regulation, Databases, Genetic, Image Processing, Computer-Assisted, Genetics, Gene chip analysis, Cluster Analysis, Humans, Segmentation, Artificial intelligence, Noise (video), Microarray image, business, Molecular Biology, Algorithms, Oligonucleotide Array Sequence Analysis |
| الوصف: | Microarray technology is a powerful tool for human genetic research and other biomedical applications. Numerous improvements to the standard K-means algorithm have been carried out to complete the image segmentation step. However, most of the previous studies classify the image into two clusters. In this paper, we propose a novel K-means algorithm, which first classifies the image into three clusters, and then one of the three clusters is divided as the background region and the other two clusters, as the foreground region. The proposed method was evaluated on six different data sets. The analyses of accuracy, efficiency, expression values, special gene spots, and noise images demonstrate the effectiveness of our method in improving the segmentation quality. |
| تدمد: | 1676-5680 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0a1396f0167387d087c2a08ea1f8eeca https://doi.org/10.4238/2015.july.14.3 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....0a1396f0167387d087c2a08ea1f8eeca |
| قاعدة البيانات: | OpenAIRE |
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