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题名:
基于细胞神经网络的生物芯片图像处理
作者: 律睿慜
学位类别: 硕士
答辩日期: 2008-06-10
授予单位: 中国科学院光电技术研究所
授予地点: 光电技术研究所
导师: 王淑蓉
关键词: 生物芯片 ; 微阵列 ; 细胞神经网络 ; 倾斜校正 ; 样点定位 ; 样点分割
其他题名: Microarray Image Processing Based on Cellular Neural Networks
学位专业: 光学工程
中文摘要: 近几年生物芯片技术的快速发展对生物芯片信息处理方法提出了更高的要求:自动化程度高、准确率高、速度快。图像处理算法是生物芯片技术信息处理技术的关键。细胞神经网络(CNN)具有并行高速的特点和适于图像处理的网络结构。本文深入研究了基于CNN的生物芯片图像处理方法。 首先探讨了CNN用于生物芯片图像处理的意义。介绍了CNN数理模型、网络结构及其用于图像处理的基本思想。 然后总结了生物芯片扫描图像的特点和已有的各种处理方法,提出了一套完整的生物芯片图像处理方案,涵盖了必要的各种处理功能。根据这一方案,基于CNN设计了一系列算法。算法功能全面,包括:图像增强、倾斜校正、样点定位、样点分割以及样点信息提取。算法还具有一些已有算法不具备的特色,能够检测受污染样点、设计了新的CNN模板用于样点定位、能快速地将CNN的处理结果转化为有利于后续处理的数据。 最后利用实际的生物芯片图像对算法进行了详细的试验研究,证明该系列算法速度快、准确率高,将有助于实时生物芯片信息处理系统的研究。
英文摘要: In recent years, an unprecedented progress has been made in biochip technology,which gave more requirements for the biochip information processing technology. Image processing is the key of the biochip information processing technology. The high speed concurrent operation character and the unique network construction of Cellular Neural Networks (CNN) are quite fit for image processing. This paper gave a deep research on the application of CNN in biochip image processing. In this paper, the research motive of applying cellular neural networks in biochip image processing is discussed. The network construction character and the mathematical physics model of CNN are reviewed. The general ways and means of designing CNN algorithm for image processing is introduced. Based on the research on the property of biochip image, combined with the review of many previous algorithms, a new scheme for biochip image processing is brought forward, which includes every indispensable function. According to the scheme, a series of CNN algorithms are put forward. The algorithms are capable of image optimization, skew correction, spot identification, spot segmentation and spot information extraction. The algorithms have some features which were not existed in many previous algorithms, such as detection of contaminated spots, new CNN templates for microarray auto-gridding, translating outcome image into proper data format for bio-information analysis. The algorithms were tested in many aspects by applying them to process real biochip image. The experimental results showed the algorithms remarkably speeds up biochip image processing without deteriorating the accuracy. The algorithms may boost the real-time biochip information processing technology.
语种: 中文
内容类型: 学位论文
URI标识: http://ir.ioe.ac.cn/handle/181551/308
Appears in Collections:光电技术研究所博硕士论文_学位论文

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Recommended Citation:
律睿慜. 基于细胞神经网络的生物芯片图像处理[D]. 光电技术研究所. 中国科学院光电技术研究所. 2008.
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