Segmentation of touching cell nuclei using gradient flow tracking |
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| Authors: | G LI† T LIU†‡ J NIE L GUO J CHEN† J ZHU†‡ W XIA¶ A MARA§ S HOLLEY§ & STC WONG†‡ |
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| Affiliation: | School of Automation, Northwestern Polytechnic University, Xi'an, China;Center for Bioinformatics, Harvard Center for Neurodegeneration and Repair, Harvard Medical School, Boston, Massachusetts, U.S.A.;Functional and Molecular Imaging Center, Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts, U.S.A.;Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, Connecticut, U.S.A.;Center for Neurologic Disease, Department of Neurology, Brigham and Women's Hospital;Harvard Medical School, Boston, Massachusetts, U.S.A. |
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| Abstract: | Reliable cell nuclei segmentation is an important yet unresolved problem in biological imaging studies. This paper presents a novel computerized method for robust cell nuclei segmentation based on gradient flow tracking. This method is composed of three key steps: (1) generate a diffused gradient vector flow field; (2) perform a gradient flow tracking procedure to attract points to the basin of a sink; and (3) separate the image into small regions, each containing one nucleus and nearby peripheral background, and perform local adaptive thresholding in each small region to extract the cell nucleus from the background. To show the generality of the proposed method, we report the validation and experimental results using microscopic image data sets from three research labs, with both over-segmentation and under-segmentation rates below 3%. In particular, this method is able to segment closely juxtaposed or clustered cell nuclei, with high sensitivity and specificity in different situations. |
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| Keywords: | Gradient flow tracking image analysis nuclei segmentation touching cell zebrafish |
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