Quantification of neural images using grey difference
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Author(s)
Yu, Donggang
D. Pham, Tuan
Yan, Hong
Crane, Denis
Griffith University Author(s)
Year published
2006
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We present new algorithms for segmenting neuron im- ages which are taken from cells being grown in culture with oxidative agents. Information from changing im- ages can be used to compare changes in neurons from the Zellweger mice to those from normal mice. Im- age segmentation is the first and major step for the study of these different types of processes in neuron cells. It is difficult to do it as these neuron cell im- ages from stained fields and unimodal histograms. In this paper we develop an innovative strategy for the segmentation of neuronal cell images which are sub- jected to stains and whose histograms ...
View more >We present new algorithms for segmenting neuron im- ages which are taken from cells being grown in culture with oxidative agents. Information from changing im- ages can be used to compare changes in neurons from the Zellweger mice to those from normal mice. Im- age segmentation is the first and major step for the study of these different types of processes in neuron cells. It is difficult to do it as these neuron cell im- ages from stained fields and unimodal histograms. In this paper we develop an innovative strategy for the segmentation of neuronal cell images which are sub- jected to stains and whose histograms are unimodal. The proposed method is based on logical analysis of grey difference. Two key parameters, window width and logical threshold, are automatically extracted to be used in logical thresholding method. Spurious re- gions are detected and removed by using hierarchical filtering window. Experiment and comparison results show the efficient of our algorithms.
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View more >We present new algorithms for segmenting neuron im- ages which are taken from cells being grown in culture with oxidative agents. Information from changing im- ages can be used to compare changes in neurons from the Zellweger mice to those from normal mice. Im- age segmentation is the first and major step for the study of these different types of processes in neuron cells. It is difficult to do it as these neuron cell im- ages from stained fields and unimodal histograms. In this paper we develop an innovative strategy for the segmentation of neuronal cell images which are sub- jected to stains and whose histograms are unimodal. The proposed method is based on logical analysis of grey difference. Two key parameters, window width and logical threshold, are automatically extracted to be used in logical thresholding method. Spurious re- gions are detected and removed by using hierarchical filtering window. Experiment and comparison results show the efficient of our algorithms.
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Conference Title
Conferences in Research and Practice in Information Technology, Volume 73. Intelligent Systems for Bioinformatics 2006. Proc. 2006 Workshop on Intelligent Systems for Bioinformatics (WISB 2006)
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Copyright Statement
© 2006 Australian Computer Society Inc. The attached file is reproduced here in accordance with the copyright policy of the publisher. Use hypertext link to access the publisher's website.