光子学报, 2015, 44 (7): 0711004, 网络出版: 2015-08-25  

细胞工厂光学显微成像与图像处理技术

Optical Microscopic Imaging and Image Processing for Cell Factories
作者单位
1 长春理工大学 生命科学技术学院, 长春 130022
2 吉林农业大学 工程技术学院, 长春 130118
摘要
针对细胞工厂监控系统长工作距和大倾斜角的观测需求, 设计了一种结构简单、成像清晰的光学显微成像系统.由于获得的细胞图像光照和色彩不均、样本浑浊、细胞重叠、边界粘连较多、细胞间距不明显, 采用单尺度Retinex算法进行图像预处理, 并结合Otsu阈值分割法与K均值聚类法进行细胞图像分割处理, 最后应用改进的快速连通区域标记以及高准确度细胞计数方法进行细胞个数统计.仿真实验和实际测试结果表明: 该系统成像分辨率和清晰度均达到工程需求, 能够较清晰地辨识出培养皿中细胞的形态和分布情况.细胞显微图像处理方法取得了良好的图像增强效果, 弱化了由光照不均和样本浑浊造成的人眼视觉无法清晰分辨细胞的现象, 消除了由于图像分割不到位造成统计误差, 细胞计数准确度达到95%以上.该方法适合多种类型细胞监测与计数处理, 可满足细胞工厂实时准确监控的要求.
Abstract
A simple structure, clear imaging optical microscopic imaging system aiming at the requirement of long working distance and large tilt angle for the cell factories was designed. According to the characteristics of the cell images uneven illumination, sample turbidity, cell adhesion, cell overlap and the unobvious cell distance, the Retinex algorithm was adopt to pretreat the image, then a fast and compositive image segmentation algorithm based on the Otsu and K-means clustering was used to segmented the cell images, at last, an improved fast connected component labeling method and a rapid high precision cell counting method were applied to count the number of cells. The results of simulation experiment and actual test show that the imaging quality of the system achieved the project actual requirements for resolution and definition, and the morphological and distribution of cells in culture dish could be identified clearly. The cell microscopic image processing method has a good image enhancement effect, weakens the phenomenon caused by the uneven illumination and sample turbidity that human vision cannot clearly distinguish the cell, and eliminates the statistical error caused by that image segmentation is not in place. The cell counting accuracy is above 95%. The method is suitable for various cells, which can meet the requirements of real-time and off-line monitoring for cell factories.
参考文献

[1] 马相虎, 沈谊清, 杨月莲等.细胞工厂自动化操作系统在水痘疫苗生产中的应用[J]. 中国新药杂志, 2014, 23(20): 2446-2449.

    MA Xiang-hu, SHEN Yi-qing, YANG Yue-lian, et al. Application of ACFM in varicella vaccine production[J]. Chinese Journal of New Drugs, 2014, 23(20): 2446-2449.

[2] 姚保利, 雷铭, 薛彬等. 高分辨和超分辨光学成像技术在空间和生物中的应用[J]. 光子学报, 2011, 40(11): 1607-1618.

    YAO Bao-li, LEI Ming, XUE Bin, et al. Process and applications of high-resolution optical imaging in space and biology[J]. Acta Photonica Sinica, 2011, 40(11): 1607-1618.

[3] 支绍韬, 章海军, 张冬仙.基于大数值孔径环形光椎照明的超分辨光学显微成像方法研究[J].物理学报, 2012, 61(2): 0242071.

    ZHI Shao-tao, ZHANG Hai-jun, ZHANG Dong-xian. Super-resolution optical microscopic imaging method based on annular illumination with high numerical aperture[J]. Acta Physica Sinica, 2012, 61(2): 0242071.

[4] 李琦, 向阳, 谷俊达, 等.细胞工厂显微监测装置的光学设计[J].中国激光, 2014, 41(10): 1-6.

    LI Qi, XIANG Yang, GU Jun-da, et al. Optical design of “cell factory” microscopic monitoring device[J]. Chinese Journal of Lasers, 2014, 41(10): 1-6.

[5] 邹爽, 许忠保, 吕清花.大景深显微成像方法研究[J].光电工程, 2013, 40(5): 120-126.

    ZUO Shuang, XU Zhong-bao, LV Qing-hua. Extension characteristics of the depth of field for microscopic system[J]. Opto-Electronic Engineering, 2013, 40(5): 120-126.

[6] 日本taitec公司细胞监控系统[EB/OL]. (2011-1-10)[2014-02-03]. http: //taitec.net/products/products-info.php.

[7] 储昭辉, 汪荣贵, 张璇, 等.基于Retinex理论JPEG2000压缩图像增强方法[J].光子学报, 2012, 41(2): 200-204.

    CHU Zhao-hui, WANG Rong-gui, ZHANG Xuan, et al. Enhancement method of JPEG2000 compressing image based on retinex theory[J]. Acta Photonica Sinica, 2012, 41(2): 200-204.

[8] 张鹏, 张志辉. 基于分段直方图变换的图像非线性增强[J].光子学报, 2014, 43(1): 0110002.

    ZHANG Peng, ZHANG Zhi-hui. Image nonlinear enhancement based on subsection histogram transform[J]. Acta Photonica Sinica, 2014, 43(1): 0110002.

[9] LIN Zhong-hua. The cell Image segmentation based on the K-L transform and OTSU method[C]. International Conference on Multimedia and Signal Processing(CMSP), 2011: 25-28.

[10] 伍春洪, 付国亮. 一种基于图像分割及邻域限制与放松的立体匹配方法[J]. 计算机学报, 2011, 34(4): 755-760.

    WU Chun-hong, FU Guo-liang. A stereo matching method based on K-means segmentation and neighborhood constraints relaxation[J]. Chinese Journal of Computers, 2011, 34(4): 755-760.

[11] ALAIN P, HERV D, PAUL M. Automated image segmentation: issues and applications[J]. Medical Imaging Systems Technology, 2005: 195-243.

[12] DE M C A. An interactive algorithm for image smoothing and segmentation[J]. Computer Vision and Image Analysis, 2009: 17-49.

[13] 高静.基于形态学分水岭算法的细胞图像分割[D].吉林: 吉林大学, 2008, 5: 65-71.

    GAO Jing. The segmentation of cells image based on the morphological watershed algorithm[D].Jilin: Jilin University .2008, 5: 65-71.

[14] 谢勤, 于小卉. 一种基于Matlab的血红细胞计数的工程方法[J]. 中南民族大学学报(自然科学版), 2013, 32(4): 69-72.

    XIE Qin, YU Xiao-hui. An engineering way for red blood cells counting based on Matlab[J]. Journal of South-Central University for Nationalities (Nation Science Edition), 2013, 32(4): 69-72.

[15] WANG Hai-jun, LIU Ming. Medical images segmentation using active contours driven by global and local image fitting energy[J]. Image Grap, 2012, 12(2): 1-15.

[16] 赵欣欣.生物组织显微图像中的细胞计数方法[D].湖北: 华中科技大学, 2012: 78-85.

    ZHAO Xin-xin. A cell counting method for microscopic image of biological tissues[D]. Hubei: Huazhong University of Science & Technology, 2012: 78-85.

[17] 程揭章, 嵇晓强, 李明光.密集型细胞显微图像高准确度快速计数方法[J].长春理工大学学报(自然科学版), 2014, 37(2): 71-75.

    CHENG Jie-zhang, JI Xiao-qiang, LI Ming-guang. Method of high precision and fast counting for Intensive cell microscopic image[J]. Journal of Changchun University of Science and Technology (Natural Science Edition), 2014, 37(2): 71-75.

[18] 苏茂君, 王兆滨, 张红娟, 等 基于PCNN自动波特征的血细胞图像分割和计数方法[J].中国生物医学工程学报, 2009, 28(1): 145-152.

    SU Mao-jun, WANG Zhao-bin, ZHANG Hong-juan, et al. A new method for blood cell image segmentation and counting based on PCNN and it′s auto move characteristic[J]. Journal of Biomedical Engineering, 2009, 28(1): 145-152.

[19] DUAN Jun, YU Le. A WBC segmentation method based on HSI color space[C]. 2011 4th IEEE International Conference on Broadband Network and Multimedia Technology (IC-BNMT).2011: 629-632.

[20] PENG Ren, HU Shang-liang, ZHU Hui-ping. Application of improved fuzzy c-means clustering in cell Image segmentation[C]. 2011 5th International Conference on Bioinformatics and Biomedical Engineering (iCBBE), 2011: 1-4.

嵇晓强, 程揭章, 李琦, 宫平, 郭瑞鹃, 于源华. 细胞工厂光学显微成像与图像处理技术[J]. 光子学报, 2015, 44(7): 0711004. JI Xiao-qiang, CHENG Jie-zhang, LI Qi, GONG Ping, GUO Rui-juan, YU Yuan-hua. Optical Microscopic Imaging and Image Processing for Cell Factories[J]. ACTA PHOTONICA SINICA, 2015, 44(7): 0711004.

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!