Prior knowledge based fast imaging for scanning ion conductance microscopy

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	Prior knowledge based fast imaging for scanning ion conductance microscopy
	Li P(李鹏); Zhang CL(张常麟); Liu LQ(刘连庆); Wang YC(王越超); Wejinya, Uchechukwu C.; Li GY(李广勇)
	2013
会议日期	July 9-12, 2013
会议地点	Wollongong, NSW, Australia
关键词	Image Reconstruction Intelligent Mechatronics Knowledge Based Systems Microelectrodes Silicones
页码	89-93
英文摘要	Scanning ion conductance microscopy (SICM) has becomes prevalent especially in probing biological samples taking advantage of its non-contact, force free, high resolution imaging ability. There are at least two imaging modes of SICM - continuous mode and hopping mode. In both imaging modes, the low imaging speed is the common disadvantage that hinders the efficiency of SICM based observation. In this paper, we propose a prior knowledge based fast imaging method to mitigate this problem. The key idea is to achieve a high resolution image on targeted features by scanning the sample twice, the first scan to obtain prior knowledge on targeted features with low resolution and the second scan to obtain images on targeted features with high resolution. In the first scan, the scanning speed can be very fast because the prior knowledge can be obtained from a low resolution image that requires few scanning points. In the second scan, only the interested areas (targeted features) are scanned. Because the scanning area on targeted features is much smaller than the whole scanning region, it takes much less time to obtain high resolution images on targeted features, As a result, the total time to acquire a high resolution is much less than the conventional one scan method. To verify the effectiveness of our proposed method, we performed high-resolution imaging on polydimethylsiloxane grating and microelectrode samples using a home-made SICM. The experimental results demonstrate the increased efficiency of SICM based observation using the twice scan method. © 2013 IEEE.
源文献作者	IEEE RAS; IEEE IES; ASME; DSC; University of Wollongong
产权排序	1
会议录	2013 IEEE/ASME International Conference on Advanced Intelligent Mechatronics: Mechatronics for Human Wellbeing, AIM 2013
会议录出版者	IEEE Computer Society
会议录出版地	Washington, United States
语种	英语
ISBN号	978-1-4673-5319-9
WOS记录号	WOS:000328705300015
内容类型	会议论文
源URL	[http://ir.sia.cn/handle/173321/13923]
专题	沈阳自动化研究所_机器人学研究室
通讯作者	Liu LQ(刘连庆)
作者单位	1.Department of Mechanical Engineering, University of Arkansas, Fayetteville, AK 72701, United States 2.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China 3.University of Chinese Academy of Sciences, China 4.Department of Mechanical and Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong 5.Department of Electrical and Computer Engineering, University of Pittsburgh, United States
推荐引用方式 GB/T 7714	Li P,Zhang CL,Liu LQ,et al. Prior knowledge based fast imaging for scanning ion conductance microscopy[C]. 见:. Wollongong, NSW, Australia. July 9-12, 2013.