Several protein crystallization techniques, including the vapor diffusion method, lend themselves well to automation techniques. Up unitl the present time, automation techniques have been restricted to setting up crys...
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Several protein crystallization techniques, including the vapor diffusion method, lend themselves well to automation techniques. Up unitl the present time, automation techniques have been restricted to setting up crystallization experiments, and procedures to monitor and analyze the experiments have not been developed. These procedures require additional hardware for video monitoring of crystallization chambers and automatic recognition of protein crystals. An automated image acquisition and analysis system makes use of both image processing routines and patternrecognition procedures. In order to design and implement such a system, we are presently developing algorithms which can recognize and locate protein crystals in video images of crystallization droplets. images of crystallization experiments are acquired and digitized, and analyses of the droplet images are conducted on the microcomputer which also acts as a host in our laboratory robotics system. We describe here our current progress in designing the imageanalysis system, including the development of appropriate patternrecognition methods. In addition, the usefulness of various patternrecognition schemes for monitoring the progress of crystallization is explored.
Electrophoresis gel analysis is a viable technique for determining the purity of hybrid corn seeds. Visually analyzing the electrophoretic gel images is a very tedious and time-consuming task. In this paper, a compute...
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ISBN:
(纸本)0897913728
Electrophoresis gel analysis is a viable technique for determining the purity of hybrid corn seeds. Visually analyzing the electrophoretic gel images is a very tedious and time-consuming task. In this paper, a computer vision system integrating image processing and patternrecognition techniques with domain-specific structural information to automate the electrophoresis gel scoring procedure is presented. A set of image processing algorithms are developed to perform extraction of the region of interest, segmentation of samples, identification of bands within samples, and final classification of different types of seeds. The image processing algorithms utilize the structural information and operator expertise to achieve high classification rate with fuzzy and incomplete information contained on the electrophoresis gels. The developed technique clearly demonstrates the potential of using computer vision in automating the gel scoring procedure. The developed technology may also be extended to other areas such as general one-dimensional electrophoresis and high performance thin layer chromatography.
An algorithm is described for reconstructing the surface shape of a non-rigid transparent object, such as water, from the apparent motion of the observed pattern. This algorithm is based on the optical and statistical...
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ISBN:
(纸本)0818620579
An algorithm is described for reconstructing the surface shape of a non-rigid transparent object, such as water, from the apparent motion of the observed pattern. This algorithm is based on the optical and statistical analysis of the distortions. It consists of the following parts: (1) extraction of optical flow, (2) averaging of each point trajectory obtained from the optical flow sequence, (3) calculation of the surface normal using optical characteristics, and (4) reconstruction of the surface. The algorithm is applied to synthetic and real images to demonstrate its performance.
Electrophoresis gel analysis is a viable technique for determining the purity of hybrid corn seeds. Visually analyzing the electrophoretic gel images is a very tedious and time-consuming task. In this paper, a compute...
ISBN:
(纸本)9780897913720
Electrophoresis gel analysis is a viable technique for determining the purity of hybrid corn seeds. Visually analyzing the electrophoretic gel images is a very tedious and time-consuming task. In this paper, a computer vision system integrating image processing and patternrecognition techniques with domain-specific structural information to automate the electrophoresis gel scoring procedure is presented. A set of image processing algorithms are developed to perform extraction of the region of interest, segmentation of samples, identification of bands within samples, and final classification of different types of *** image processing algorithms utilize the structural information and operator expertise to achieve high classification rate with fuzzy and incomplete information contained on the electrophoresis gels. The developed technique clearly demonstrates the potential of using computer vision in automating the gel scoring procedure. The developed technology may also be extended to other areas such as general one-dimensional electrophoresis and high performance thin layer chromatography.
It is a focus of discussion whether flow cytometry or imageanalysis reaches the goal of automated cytology. For a patternrecognition the authors applied linear type CCD possessing 2048 sensor elements. Digitized dat...
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It is a focus of discussion whether flow cytometry or imageanalysis reaches the goal of automated cytology. For a patternrecognition the authors applied linear type CCD possessing 2048 sensor elements. Digitized data accumulated into NOVA 3 by 1 micron scanning could take various parameters into account such as area, total density, density distribution, nuclear shape, nuclear circumference and N/C ratio. Rapidity and accuracy were compared with flow cytometry using Feulgen stained cultured cancer cells in administration of Adriamycin (0. 5 mu g/ml). Its effect on the cell cycle was well correlated in histograms. Secondly, discrimination of in situ cancer cells from dysplastic cells in sputum based on high resolution with various parameters could be performed according to a linear discriminant function (Mahalanobis' distance).
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