摘要
蜂窝状堆叠数字PCR微阵列图像因其单元尺寸小、排列密集,荧光信号弱、易受光照分布影响,其样点定位困难。本文提出基于形态学的三通道蜂窝状荧光图像样点寻址算法及数字PCR图像信息提取方法,可快速、有效识别微阵列芯片生物分子微弱荧光信息。针对不同通道的图像进行配准融合,使样点排布整齐;通过增强图像的对比度,选取有效样点区域,基于改进伽马算法去除光照分布不均效应;基于形态学算法识别紧密排列的样点,对微阵列芯片图像进行单元分割定位,提取每个样点的生物分子荧光信息。该方法处理一块约20000个微单元的数字PCR芯片图像的耗时小于20 s,与现有定位方法相比,处理相同数量样点的图片的耗时可减少3个数量级;通过与标准仪器结果相比,样点识别精度达到98.79%,生物信息计算结果(拷贝数)准确度达到96.2%。本文提出基于形态学的三通道蜂窝状荧光图像样点寻址算法及数字PCR图像信息提取方法克服了蜂窝状堆叠式微阵列荧光图像样点难以定位的问题,与现有方法相比,能够快速、准确地获取生物信息,为数字PCR技术的精准定量奠定了基础。
Due to its small unit size,dense array,weak fluorescence signal,and vulnerability to light distribution,it is difficult to locate the sample points of honeycomb stacked digital PCR microarray images.In this paper,an algorithm of three-channel honeycomb fluorescence spots addressing based on morphology,and a digital PCR image information extraction method are proposed,which can quickly and effectively identify the weak fluorescence information of biomolecules in microarray chips.The image registration fusion is carried out for different channels to make the sample points orderly.Select effective spots area by enhancing the contrast of the image.Use improved gamma algorithm to remove uneven distribution of illumination.Identify,locate and segment the closely arranged spots on the microarray chip based on morphological algorithm,and then,extract the fluorescence information of biomolecules of each spot.Using this method,the image processing time of a digital PCR chip with about 20000 microcells is less than 20 s.Compared with the existing spot addressing methods,the processing time of the same number of samples can be reduced by three orders of magnitude.Compared with the results of standard instruments,the accuracy of sample recognition is 98.79%,and the accuracy of biological information calculation(copy number)is 96.2%.In this paper,the three-way honeycomb fluorescence spot addressing algorithm and digital PCR image information extraction method based on morphology are proposed to overcome the difficulty of locating the spots in the honeycomb stacked microarray fluorescence picture.Compared with the existing methods,biological information can be obtained quickly and accurately,which lays a foundation for precise quantification of digital PCR technology.
作者
李树力
李金泽
郭振
朱文艳
周连群
张芷齐
LI Shu-li;LI Jin-ze;GUO Zhen;ZHU Wen-yan;ZHOU Lian-qun;ZHANG Zhi-qi(School of Communication and Information Engineering,Shanghai University,Shanghai 200444,China;Key Laboratory of Bio-medical Diagnostics of Chinese Academy of Sciences,Suzhou Institute of Biomedical Engineering and Technology,Chinese Academy of Sciences,Suzhou 215163,China;University of Science and Technology of China,Hefei 230026,China)
出处
《光学精密工程》
EI
CAS
CSCD
北大核心
2020年第12期2745-2755,共11页
Optics and Precision Engineering
基金
国家重点研发计划资助项目(No.2018YFC0115705)
国家自然科学基金资助项目(No.51675517,No.61874133,No.61901469)
江苏省重点研究开发项目(No.BE2019684,No.BE2018080)
季华实验室资助项目(No.X190181TD190)
中科院青年创新促进会资助项目(No.2019322,No.2018360,No.Y201856)
中国科学院STS项目(No.KFJ-STS-SCYD-217,No.KFJ-STS-ZDTP-061)
中国科学院仪器装备项目(No.YJKYYQ20190057)
苏州市科技支撑计划资助项目(No.SYG201907)
济南市“高校20条”资助项目(No.2018GXRC030)
天津科学与技术工程资助项目(No.19YFYSQY00040)。
关键词
生物荧光图像
蜂窝状
数字PCR微阵列
寻址定位
bioluminescent image
honeycomb
digital polymerase chain reaction microarray
spot addressing
