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An Automated Method for Cell Detection in Zebrafish

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Abstract

Quantification of cells is a critical step towards the assessment of cell fate in neurological disease or developmental models. Here, we present a novel cell detection method for the automatic quantification of zebrafish neuronal cells, including primary motor neurons, Rohon–Beard neurons, and retinal cells. Our method consists of four steps. First, a diffused gradient vector field is produced. Subsequently, the orientations and magnitude information of diffused gradients are accumulated, and a response image is computed. In the third step, we perform non-maximum suppression on the response image and identify the detection candidates. In the fourth and final step the detected objects are grouped into clusters based on their color information. Using five different datasets depicting zebrafish cells, we show that our method consistently displays high sensitivity and specificity of over 95%. Our results demonstrate the general applicability of this method to different data samples, including nuclear staining, immunohistochemistry, and cell death detection.

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Acknowledgements

The software and sample dataset used in this paper are released at the website: http://www.cbi-platform.net/. We would like to thank Dr. William Campbell, Jacqueline Sears and Melvin Zhang for zebrafish image acquisition and analysis, and thank Dr. Scott Holley for providing the zebrafish images in Fig. 11. This work is funded by the NIH AG015379 (WX) and a Bioinformatics Research Center Program Grant from HCNR (STCW).

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Authors and Affiliations

  1. The Center for Biomedical Informatics, The Methodist Hospital Research Institute, Houston, TX, USA

    Tianming Liu, Gang Li, Ashley Tarokh, Xiaobo Zhou & Stephen T. C. Wong

  2. Department of Radiology, The Methodist Hospital, Weill Cornell Medical College, Houston, TX, USA

    Tianming Liu, Ashley Tarokh, Xiaobo Zhou & Stephen T. C. Wong

  3. School of Automation, Northwestern Polytechnical University, Xi’an, China

    Gang Li, Jingxin Nie & Lei Guo

  4. Department of Ophthalmology, Harvard Medical School, Boston, MA, USA

    Jarema Malicki

  5. Center for Neurologic Disease, Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Weiming Xia

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  1. Tianming Liu
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Correspondence to Stephen T. C. Wong.

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Liu, T., Li, G., Nie, J. et al. An Automated Method for Cell Detection in Zebrafish. Neuroinform 6, 5–21 (2008). https://doi.org/10.1007/s12021-007-9005-7

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