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    盛宙, 颜秉勇, 周家乐, 王慧锋. 基于模糊C均值和SLIC的纳米孔阻断事件的识别与研究[J]. 华东理工大学学报(自然科学版), 2020, 46(1): 100-113. DOI: 10.14135/j.cnki.1006-3080.20181206002
    引用本文: 盛宙, 颜秉勇, 周家乐, 王慧锋. 基于模糊C均值和SLIC的纳米孔阻断事件的识别与研究[J]. 华东理工大学学报(自然科学版), 2020, 46(1): 100-113. DOI: 10.14135/j.cnki.1006-3080.20181206002
    SHENG Zhou, YAN Bingyong, ZHOU Jiale, WANG Huifeng. Detection and Research on Blockade Events of Nanopore Current Based on Fuzzy C-Means and SLIC[J]. Journal of East China University of Science and Technology, 2020, 46(1): 100-113. DOI: 10.14135/j.cnki.1006-3080.20181206002
    Citation: SHENG Zhou, YAN Bingyong, ZHOU Jiale, WANG Huifeng. Detection and Research on Blockade Events of Nanopore Current Based on Fuzzy C-Means and SLIC[J]. Journal of East China University of Science and Technology, 2020, 46(1): 100-113. DOI: 10.14135/j.cnki.1006-3080.20181206002

    基于模糊C均值和SLIC的纳米孔阻断事件的识别与研究

    Detection and Research on Blockade Events of Nanopore Current Based on Fuzzy C-Means and SLIC

    • 摘要: 纳米孔电流信号的分析依赖于对不同类型的阻断事件的准确分析。在阻断事件提取上,提出了一种基于灰度图检测阻断事件的新方法,对灰度图进行二值化后提取出阻断事件。针对基线电流对二值化阈值选取的影响,采用从小波分解后的近似系数中估计出基线电流的方法实现自适应的二值化阈值。为了减小阈值法对检测出的短阻断事件起始与终止位置的影响,采用模糊C均值(Fuzzy C-Means,FCM)方法对短阻断事件的位置进行修正。对检测出的多级事件,先将其转换为相应的具有颜色差异的灰度图,再利用简单的线性迭代聚类(Simple Linear Iterative Clustering,SLIC)超像素算法对多级事件的台阶自动检测。为避免SLIC算法的过分割带来属于同一台阶的超像素被分割的问题,对过度分割后的超像素进行超像素融合,实现属于同一台阶的超像素融合。仿真结果表明,基于灰度图的事件检测方法能够实现对信号中阻断事件的有效检测,FCM算法能够实现对短阻断事件位置的有效修正,SLIC超像素算法能够有效地检测出多级事件的台阶数。

       

      Abstract: The analysis of nanopore signal depends on the exact extraction of short and multi-level blockade events. In this paper, a new method based on grayscale is proposed to detect short and multi-level events from signal automatically. In order to reduce the interferences of noise and avoid the distortion of events via the low-pass filter, the wavelet decomposition is used to achieve the denoising of signal. And then, the denoised signal is used to generate the grayscale in which the color of blockage events differs from that of baseline. The blockade events can be extract from the grayscale by thresholding the grayscale. Short-events extracted by threshold often have shorter length. To deal with this problem, this paper utilizes fuzzy C-means(FCM) to recover the extracted short events. Compared with second-order differential method (DBC) and full width half maximum (FWHM) , the FCM can recover the short event more precisely. Multi-level events are processed by converted to grayscale without thresholding. The pixels from different levels are different and these pixels with the same level are similar. These similar pixels can be regarded as one superpixel. By counting the number of different superpixels, we can obtain the levels of the multi-level events. To get the different superpixel from the grayscale automatically, this paper introduces simple linear iterative clustering (SLIC) to split the graysacle into several superpixels. Meanwhile, we can also obtain the starting point, ending point, and the average pixel value from split superpixels. Since SLIC is sensitive to the number of cluster centers, the number of cluster center may be different for different multi-level events. To avoid this shortcoming, we set the number of cluster center as 10 to cover the most cases of multi-level events. After getting the over-splite superpixels, we utilize superpixel fusion to connect two adjacent superpixels belonging to the same level by comparing the average pixel value of each superpixel. It is shown from the simulation that the SLIC superpixel fusion can obtain the accurate number of superpixels that is the same as the one of multi-level events.

       

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