【24h】

Image Sifting for Micro Array Image Enhancement

机译:用于微阵列图像增强的图像筛选

获取原文
获取原文并翻译 | 示例

摘要

cDNA micro arrays are more and more frequently used in molecular biology as they can give insight into the relation of an organism's metabolism and its genome. The process of imaging a micro array sample can introduce a great deal of noise and bias into the data with higher variance than the original signal which may swamp the useful information. As imperfections and fabrication artifacts often impair our ability to measure accurately the quantities of interest in micro array images, image processing for analysis of these images is an important and challenging problem. How to eliminate the effect of the noise imposes a challenging problem in micro array analysis. In this paper we implemented a novel algorithm for image sifting which could remove objects with definite size from macro array images. We used regular moving grids to sift noise object and obtained clean images for segmentation. The results have been compared with SWT, DWT and wiener filter denoising.
机译:cDNA微阵列在分子生物学中越来越常用,因为它们可以洞察生物的代谢与其基因组之间的关系。对微阵列样本进行成像的过程会以比原始信号更高的方差向数据中引入大量噪声和偏差,从而可能淹没有用的信息。由于缺陷和制造伪影通常会削弱我们准确测量微阵列图像中感兴趣的量的能力,因此用于分析这些图像的图像处理是一个重要且具有挑战性的问题。如何消除噪声的影响在微阵列分析中提出了一个具有挑战性的问题。在本文中,我们实现了一种新颖的图像筛选算法,该算法可以从宏数组图像中删除具有确定大小的对象。我们使用规则的移动网格来筛选噪声对象,并获得清晰的图像进行分割。将结果与SWT,DWT和维纳滤波器去噪进行了比较。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号