实时图像处理及其在医学中的应用
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摘要
本文提出了一种利用高性能图像采集卡在不使用DSP的情况下实现实时图像处理的方法。并将该技术应用于医学领域，对培养瓶中生长的心肌细胞的搏动情况进行实时记录，研制出一套心肌细胞搏动情况自动分析处理系统。主要工作包括以下几个方面：
1、详细论述了在WINDOWS操作系统下开发实时系统需要掌握的有关技术。介绍了图像采集卡和CCD摄像机的工作原理。结合MeteorⅡ和Domino-Mini两块图像卡的特性详尽说明了用它们实现实时图像处理的具体步骤。并对用高性能图像采集卡实现实时图像处理进行了经验总结。
2、简单介绍了动态图像处理的意义和一般方法。在此基础上介绍了如何用减影法进行图像处理，并对它进行改进提出了检测心肌细胞序列图像运动特征的一种方法。给出了实验数据曲线和结果分析，并对这种方法的优缺点进行了总结。
3、介绍了序列图像中相关跟踪方法的原理，改进了原有快速相关算法并用最小二乘曲面拟合的方法来得到亚像素的定位精度。用相关方法对心肌细胞序列图像进行处理，给出了实验数据曲线和结果分析。
4、研究光流法在动态图像处理中的应用，给出初步结果。以Visual C++6.0为开发环境，开发出运行于Windows 2000／NT下，具有良好用户界面、可靠稳定的软件系统，并设计了一个封装图像采集卡功能的类。
实验表明，本系统完全可以达到图像处理实时性的要求，对心肌细胞序列图像的处理结果也是令人满意的。
This thesis bring forward a method to realize real-time image processing without using DSP but using high quality image grabber instead. Based on this technology, an automatic analysis and processing system, which can take the real-time record of the pulsation of myocardial cells growing in the culture flask, is designed and has been applied in the medical field already.
The thesis is divided into 4 sections: Section I gives a detailed examination of the techniques relevant to real-time system developing under WINDOWS. This section also includes the operating principles of image grabber and CCD camera, an elaborate explanation of the concrete procedures of real-time image processing realized by image grabber Meteor I] and Domino-Mini, and an empirical summary
on the real-time image processing realized by these high-quality image grabber. Section II attempts to introduce the significance of dynamic image processing and the oft-adopted methods. We focus our attention on how to process image with difference and bring forward a method analyzing the movement properties of the myocardial cells image sequences by the means of improving it. Finally, we provide
an analysis of the experimental data with the pros and cons report followed. Section III begins with the principles of correlation tracking in image sequences, and then improves former swift correlation algorithm and achieves location precision of sub-pixel by using least-square-surface-fit method. Thus we manage myocardial cells image sequences with correlation and finally offer an analysis of the
experimental data and the conclusion as well. Section IV studies the applications of optical flow in dynamic image processing and demonstrates the results in first stage. In this section, we also illustrate a system with a friendly users interface we developed with Visual C++ 6.0, which proves to be capable of running stably under Windows 2000/NT. A class encapsulating functions of image grabber is designed, too.
Experiments show that the system can well meet the real-time requirements of image processing and the results of the processing of the image of myocardial cells order are also satisfactory.
1、详细论述了在WINDOWS操作系统下开发实时系统需要掌握的有关技术。介绍了图像采集卡和CCD摄像机的工作原理。结合MeteorⅡ和Domino-Mini两块图像卡的特性详尽说明了用它们实现实时图像处理的具体步骤。并对用高性能图像采集卡实现实时图像处理进行了经验总结。
2、简单介绍了动态图像处理的意义和一般方法。在此基础上介绍了如何用减影法进行图像处理，并对它进行改进提出了检测心肌细胞序列图像运动特征的一种方法。给出了实验数据曲线和结果分析，并对这种方法的优缺点进行了总结。
3、介绍了序列图像中相关跟踪方法的原理，改进了原有快速相关算法并用最小二乘曲面拟合的方法来得到亚像素的定位精度。用相关方法对心肌细胞序列图像进行处理，给出了实验数据曲线和结果分析。
4、研究光流法在动态图像处理中的应用，给出初步结果。以Visual C++6.0为开发环境，开发出运行于Windows 2000／NT下，具有良好用户界面、可靠稳定的软件系统，并设计了一个封装图像采集卡功能的类。
实验表明，本系统完全可以达到图像处理实时性的要求，对心肌细胞序列图像的处理结果也是令人满意的。
This thesis bring forward a method to realize real-time image processing without using DSP but using high quality image grabber instead. Based on this technology, an automatic analysis and processing system, which can take the real-time record of the pulsation of myocardial cells growing in the culture flask, is designed and has been applied in the medical field already.
The thesis is divided into 4 sections: Section I gives a detailed examination of the techniques relevant to real-time system developing under WINDOWS. This section also includes the operating principles of image grabber and CCD camera, an elaborate explanation of the concrete procedures of real-time image processing realized by image grabber Meteor I] and Domino-Mini, and an empirical summary
on the real-time image processing realized by these high-quality image grabber. Section II attempts to introduce the significance of dynamic image processing and the oft-adopted methods. We focus our attention on how to process image with difference and bring forward a method analyzing the movement properties of the myocardial cells image sequences by the means of improving it. Finally, we provide
an analysis of the experimental data with the pros and cons report followed. Section III begins with the principles of correlation tracking in image sequences, and then improves former swift correlation algorithm and achieves location precision of sub-pixel by using least-square-surface-fit method. Thus we manage myocardial cells image sequences with correlation and finally offer an analysis of the
experimental data and the conclusion as well. Section IV studies the applications of optical flow in dynamic image processing and demonstrates the results in first stage. In this section, we also illustrate a system with a friendly users interface we developed with Visual C++ 6.0, which proves to be capable of running stably under Windows 2000/NT. A class encapsulating functions of image grabber is designed, too.
Experiments show that the system can well meet the real-time requirements of image processing and the results of the processing of the image of myocardial cells order are also satisfactory.
引文
[1] K. R. Castleman, 数字图像处理，电子工业出版社，1999
[2] 孙即祥，数字图像处理，河北教育出版社，1993
[3] 王润生，图像理解，国防科技大学出版社，1995
[4] 熊江辉，模拟失重影响心肌收缩功能的机理研究—NO和细胞骨架作用途径，硕士学位论文，1999．1
[5] 贾云得，机器视觉，科学出版社，2000．4
[6] 高文、陈熙霖，计算机视觉，清华大学出版社，1999．2
[7] 马颂德、张正友，计算机视觉—计算理论与算法基础，科学出版社，1998．1
[8] 郑南宁，计算机视觉与模式识别，国防工业出版社，1998．3
[9] 张云生，实时控制系统软件设计原理及应用，国防工业出版社，2000．10
[10] 李智勇等，动态图像分析，国防工业出版社，1999．8
[11] 李大琛，着陆冲击真彩色序列图像目标跟踪定位方法与研究，国防科学技术大学硕士论文，1999．10
[12] 陆宏伟，数字式靶场图像自动分析系统，国防科学技术大学硕士论文，2000．1
[13] 邱志强，从透视图像恢复刚体三维运动参数的理论与方法研究，国防科学技术大学硕士论文，2000．1
[14] 伏思华等，利用双缓冲实现实时图像处理，国防科技大学首届研究生学术活动周，2001．11
[15] 张远鹏等，计算机图像处理技术基础，北京大学出版社，1996
[16] 朱伯春，双片TMS320C40并行实时图像处理系统，通信学报，1998
[17] Domino-Mini图像采集卡用户指南，1999
[18] 刘国锋、诸昌钤，光流的计算技术，西南交通大学学报，1997．12
[19] 陈海峰、陈维南，基于区域平滑约束的光流场估计方法，高技术通讯，1998．9
[20] Phillip A.Laplante,Real-Time Signal and Image Processing Selected Readings,IEEE
[21] J.LBarron and A.Liptay,Optical Flow to Measure Minute Increments in Plant Growth
[22] Horn B K P,Schunck B G.,Determining optical flow,Artificial Intelligence,1981,17, 185-204
[23] VerriA,Girosi F,Torre V,Differential techniques for optical flow,J.Opt.Soc.Am,1990,A7:912-922
[24] Singh A,Allen P,Image-flow computation:an estimation-theoretic framework and a unified perspective,CVGIP:Image Understanding,19
[25] Grossberg S,Mingollaa E,Neural dynamics of visual motion perception:local detection and global grouping In:Carpenter G A,Grossberg S eds,Neural networks for vision and image processing,Massachusetts:MIT Press,1992:293-342
[26] 李介谷，图像处理技术，上海交通大学出版社，1988
[27] 章毓晋，图像处理和分析，清华大学出版社，1999
[29] 潘爱民等译，Visual C++技术内幕，清华大学出版社，1995
[30] 于起峰，基于图像的精密测量技术，科学出版社，待出版
[31] 王华等，Visual C++编程技巧与实例，机械工业出版社，1999．4
[32] 郑人杰，软件工程，清华大学出版社，1999．8
[33] John E.Swanke,Visual C++MFC扩展编程实例，机械工业出版社，2000．3
[34] Robert L.Libbey,信号与图像处理，电子工业出版社，1997．1
[35] 薛天跃、李萍，从光流场计算刚体运动参数，太原重型机械学院学报，Vol．20 No．1 1999．3
[36] 万海峰、傅玉川、王植恒，激光散斑图样的光流场分析研究，光学学报， Vol．17 No．4 1997．4
[37] 薛天跃、师子源，斜投影光流场刚体三维运动和结构计算，太原重型机械学院学报，Vol．20 No．2 1999．6
[38] 崔东明，自发光流场的光学显示与测量，弹道学报，Vol．10 No．3 1998．9
[39] Aisbett,J, Optical flow with an intensity-smoothing, IEEE Tansactions on Pattern Analysis and Machine Intelligence, 11(5):512-522
[40] Black,M.J. and Jepson, A.D, Estimating optical flow in segmented imagcs using bariable-order parametric models with local deformatioms, IEEE Transactions on Pattern Analysis and Machic Intelligenee, 18(10):972-986.
[41] Chaudhury,K. and Mehrotra,R. A trajectory-based computational model for optical flow estimation, IEEE Transactions on Robotics and Automation, 11(5):733-741.
[42] Chin,T.M.,Karl,W.C.,and Willsky,A.S, Probabilistic and sequentialcomputation of optical flow using temporal coherence, IEEE Transactions on Image Processing, 3(6):773-788.
[43] John C.McEachen and Janes S. Duncan, Shape-Based Tracking of Left Ventricular Wall Motion, IEEE Transactions on Medical Imaging,Vol.16, No.3 1997.3
[44] 郭旭平等，跟踪系统中图像目标的快速提取技术研究，电子科技大学学报，Vol．27 No．1 1998．2
[45] 杨占昕等，一个基于MVP的实时图像处理平台，信号处理，Vol．15 No．2 1999．6
[47] 向征，一种实时计算机系统监控软件的设计，微电子与计算机，No．9 1993
[48] 谈新权等，实时图像采集卡硬件软件设计，华中理工大学学报，Vol．23 No．10 1995．10
[49] 陈朝阳、张桂林，基于图像对称差分运算的运动小目标检测方法，华中理工大
学学报，Vol．26 No．9 1998．9
[50]徐建华，图像处理与分析，北京：科学出版社，1992
[51]乔林、杨志刚，Visual C++6.0高级编程技术—MFC与多线程篇，中国铁道出版社，2000．2
[52]金观昌，计算机辅助光学测量，清华大学出版社，1997．6
[2] 孙即祥，数字图像处理，河北教育出版社，1993
[3] 王润生，图像理解，国防科技大学出版社，1995
[4] 熊江辉，模拟失重影响心肌收缩功能的机理研究—NO和细胞骨架作用途径，硕士学位论文，1999．1
[5] 贾云得，机器视觉，科学出版社，2000．4
[6] 高文、陈熙霖，计算机视觉，清华大学出版社，1999．2
[7] 马颂德、张正友，计算机视觉—计算理论与算法基础，科学出版社，1998．1
[8] 郑南宁，计算机视觉与模式识别，国防工业出版社，1998．3
[9] 张云生，实时控制系统软件设计原理及应用，国防工业出版社，2000．10
[10] 李智勇等，动态图像分析，国防工业出版社，1999．8
[11] 李大琛，着陆冲击真彩色序列图像目标跟踪定位方法与研究，国防科学技术大学硕士论文，1999．10
[12] 陆宏伟，数字式靶场图像自动分析系统，国防科学技术大学硕士论文，2000．1
[13] 邱志强，从透视图像恢复刚体三维运动参数的理论与方法研究，国防科学技术大学硕士论文，2000．1
[14] 伏思华等，利用双缓冲实现实时图像处理，国防科技大学首届研究生学术活动周，2001．11
[15] 张远鹏等，计算机图像处理技术基础，北京大学出版社，1996
[16] 朱伯春，双片TMS320C40并行实时图像处理系统，通信学报，1998
[17] Domino-Mini图像采集卡用户指南，1999
[18] 刘国锋、诸昌钤，光流的计算技术，西南交通大学学报，1997．12
[19] 陈海峰、陈维南，基于区域平滑约束的光流场估计方法，高技术通讯，1998．9
[20] Phillip A.Laplante,Real-Time Signal and Image Processing Selected Readings,IEEE
[21] J.LBarron and A.Liptay,Optical Flow to Measure Minute Increments in Plant Growth
[22] Horn B K P,Schunck B G.,Determining optical flow,Artificial Intelligence,1981,17, 185-204
[23] VerriA,Girosi F,Torre V,Differential techniques for optical flow,J.Opt.Soc.Am,1990,A7:912-922
[24] Singh A,Allen P,Image-flow computation:an estimation-theoretic framework and a unified perspective,CVGIP:Image Understanding,19
[25] Grossberg S,Mingollaa E,Neural dynamics of visual motion perception:local detection and global grouping In:Carpenter G A,Grossberg S eds,Neural networks for vision and image processing,Massachusetts:MIT Press,1992:293-342
[26] 李介谷，图像处理技术，上海交通大学出版社，1988
[27] 章毓晋，图像处理和分析，清华大学出版社，1999
[29] 潘爱民等译，Visual C++技术内幕，清华大学出版社，1995
[30] 于起峰，基于图像的精密测量技术，科学出版社，待出版
[31] 王华等，Visual C++编程技巧与实例，机械工业出版社，1999．4
[32] 郑人杰，软件工程，清华大学出版社，1999．8
[33] John E.Swanke,Visual C++MFC扩展编程实例，机械工业出版社，2000．3
[34] Robert L.Libbey,信号与图像处理，电子工业出版社，1997．1
[35] 薛天跃、李萍，从光流场计算刚体运动参数，太原重型机械学院学报，Vol．20 No．1 1999．3
[36] 万海峰、傅玉川、王植恒，激光散斑图样的光流场分析研究，光学学报， Vol．17 No．4 1997．4
[37] 薛天跃、师子源，斜投影光流场刚体三维运动和结构计算，太原重型机械学院学报，Vol．20 No．2 1999．6
[38] 崔东明，自发光流场的光学显示与测量，弹道学报，Vol．10 No．3 1998．9
[39] Aisbett,J, Optical flow with an intensity-smoothing, IEEE Tansactions on Pattern Analysis and Machine Intelligence, 11(5):512-522
[40] Black,M.J. and Jepson, A.D, Estimating optical flow in segmented imagcs using bariable-order parametric models with local deformatioms, IEEE Transactions on Pattern Analysis and Machic Intelligenee, 18(10):972-986.
[41] Chaudhury,K. and Mehrotra,R. A trajectory-based computational model for optical flow estimation, IEEE Transactions on Robotics and Automation, 11(5):733-741.
[42] Chin,T.M.,Karl,W.C.,and Willsky,A.S, Probabilistic and sequentialcomputation of optical flow using temporal coherence, IEEE Transactions on Image Processing, 3(6):773-788.
[43] John C.McEachen and Janes S. Duncan, Shape-Based Tracking of Left Ventricular Wall Motion, IEEE Transactions on Medical Imaging,Vol.16, No.3 1997.3
[44] 郭旭平等，跟踪系统中图像目标的快速提取技术研究，电子科技大学学报，Vol．27 No．1 1998．2
[45] 杨占昕等，一个基于MVP的实时图像处理平台，信号处理，Vol．15 No．2 1999．6
[47] 向征，一种实时计算机系统监控软件的设计，微电子与计算机，No．9 1993
[48] 谈新权等，实时图像采集卡硬件软件设计，华中理工大学学报，Vol．23 No．10 1995．10
[49] 陈朝阳、张桂林，基于图像对称差分运算的运动小目标检测方法，华中理工大
学学报，Vol．26 No．9 1998．9
[50]徐建华，图像处理与分析，北京：科学出版社，1992
[51]乔林、杨志刚，Visual C++6.0高级编程技术—MFC与多线程篇，中国铁道出版社，2000．2
[52]金观昌，计算机辅助光学测量，清华大学出版社，1997．6