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1.中国科学技术大学, 安徽 合肥 230026
2.中国科学院 苏州生物医学工程技术研究所, 中国科学院生物医学检验技术重点实验室, 江苏 苏州 215163
3.苏州大学 电子信息学院, 江苏 苏州 215006
4.长春理工大学 机电工程学院, 吉林 长春 130022
5.上海大学 通信与信息工程学院, 上海 200444
[ "朱文艳(1993-), 女, 河南淮阳人, 硕士研究生, 2017年于郑州大学获得学士学位, 主要从事系统控制及自动对焦方向的研究。E-mail:zhuwy@mail.ustc.edu.cn" ]
[ "姚佳(1986-), 男, 江苏苏州人, 博士, 副研究员, 2011年于南京航空航天大学获得硕士学位, 主要从事微纳生物传感器及其应用的研究。E-mail:yaojia@sibet.ac.cn" ]
收稿日期:2020-02-19,
修回日期:2020-04-16,
录用日期:2020-4-16,
纸质出版日期:2020-09-25
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朱文艳, 周连群, 张芷齐, 等. 微孔式数字PCR荧光芯片的自动对焦[J]. 光学 精密工程, 2020,28(9):2065-2075.
Wen-yan ZHU, Lian-qun ZHOU, Zhi-qi ZHANG, et al. Autofocus of microarray digital PCR fluorescent chip[J]. Optics and precision engineering, 2020, 28(9): 2065-2075.
朱文艳, 周连群, 张芷齐, 等. 微孔式数字PCR荧光芯片的自动对焦[J]. 光学 精密工程, 2020,28(9):2065-2075. DOI: 10.37188/OPE.20202809.2065.
Wen-yan ZHU, Lian-qun ZHOU, Zhi-qi ZHANG, et al. Autofocus of microarray digital PCR fluorescent chip[J]. Optics and precision engineering, 2020, 28(9): 2065-2075. DOI: 10.37188/OPE.20202809.2065.
为了快速获取微孔式数字PCR芯片清晰的荧光图像,解决传统方法针对微尺度阵列单元自动对焦存在的计算量大,耗时长等问题,建立了基于像素个数随离焦距离变化特征模型的自动对焦方法。依次取3个彼此间隔相同距离的微孔式数字PCR芯片的荧光图像,通过自适应窗口选取与阈值计算,统计窗口区域内大于阈值的像素个数,代入特征函数计算离焦距离,并通过统计出的3个位置的像素个数值判断离焦方向,继而进行对焦。该方法仅需统计13×13个像素大小的对焦窗口中灰度大于阈值的像素个数,且完成对焦仅需4步,对焦结果完全满足后续计算的清晰度要求,与传统爬山方法相比,对焦步骤数平均减少了51.89%,实现了微孔式数字PCR芯片的准确快速对焦。本文提出的自动对焦方法克服了现有算法计算量大、对焦步骤繁琐的缺点,预测准确、速度快,最大程度上减少样本曝光时间,进而减少荧光的淬灭,为后续计算提供更为原始且精确的图像。
An autofocusing method
based on the characteristic model of the number of pixels changing with the defocus distance
was proposed to quickly obtain a clear fluorescence image of a micropore digital polymerase chain reaction (PCR) chip and overcome the issue of time-consuming calculation in the traditional method for autofocusing of the microscale array unit. Thereafter
fluorescent images of three microarray digital PCR chips equidistant from each other were selected. The threshold was calculated through an adaptive window. The pixels in the window area with values larger than the threshold were counted. The defocus distance was calculated by substitution in the characteristic function. The defocus direction was determined by the pixel values of the three positions and then focusing was carried out. This method uses only statistics of values larger than the threshold of the 13×13 pixels in the focusing window and completes focusing in only four steps. The focusing results satisfied the requirements of subsequent calculations. Compared with the traditional mountain climbing method
the number of focusing steps was decreased by 51.89% on average upon the implementation of the microarray-type digital PCR chip accurate focusing. The proposed autofocus method overcomes the shortcomings of contemporary algorithms
such as extensive computation and tedious focusing steps
and provides an accurate and rapid focusing method. It minimizes the exposure time of the sample
thereby reducing fluorescence quenching
and provides more original and accurate images for subsequent calculations.
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