Tracking in molecular bioimaging

被引:137
作者
Meijering, E [1 ]
Smal, I
Danuser, G
机构
[1] Erasmus MC, Rotterdam, Netherlands
[2] Swiss Fed Inst Technol, CH-1015 Lausanne, Switzerland
[3] Eindhoven Univ Technol, Dept Math & Comp Sci, Postmaster Program Math Ind, NL-5600 MB Eindhoven, Netherlands
[4] Erasmus Univ, Rotterdam, Netherlands
[5] Marine Biol Lab, Woods Hole, MA 02543 USA
[6] Swiss Fed Inst Technol, Zurich, Switzerland
[7] Scripps Res Inst, La Jolla, CA USA
基金
美国国家卫生研究院;
关键词
D O I
10.1109/MSP.2006.1628877
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Over the past decades, a number of image analysis techniques have been developed in support of biomolecular studies. Majority of these techniques however are based on rudimentary principles. With the advent of computer vision techniques, more sophisticated tracking techniques in biological molecular imaging emerged. Currently, the most important of such techniques is light microscopy. However, achieving robustness and high accuracy in tracking and motion analysis in images obtained by light microscopy is hampered by three factors including the limited spatial resolution of the microscope, noise, and the large variability of biological image data. The latest generation of computational image analysis tools for (semi)-automated tracking of single molecules or molecular compounds within living cells promise to address these limitations. Although a number of these techniques are already available, the basic concepts uunderlying them are virtually the same. The common steps followed by these methods are as follows: preprocessing the image data, detecting individual particles per time point, linking particles detected at successive time points, and analyzing the results.
引用
收藏
页码:46 / 53
页数:8
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