A better understanding of cell behavior is very important in drug and disease research. Cell size, shape, and motility may play a key role in stem-cell specialization or cancer development. However the traditional method of inferring these values from image sequences manually is such an onerous task that automated methods of cell tracking and segmentation are in high demanded, especially given the increasing amount of cell data being collected. In this paper, a novel probabilistic cell model is designed to segment the individual hematopoietic stem cells (HSCs) extracted from mice bone marrow cells. The proposed cell model has been successfully applied to HSC segmentation, identifying the most probable cell locations in the image on the basis of cell brightness and morphology.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A probabilistic living cell segmentation model


    Contributors:
    Kachouie, N.N. (author) / Lee, L.J. (author) / Fieguth, P. (author)


    Publication date :

    2005-01-01


    Size :

    116223 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    A Probabilistic Living Cell Segmentation Model

    Kachouie, N. N. / Lee, L. J. / Fieguth, P. | British Library Conference Proceedings | 2005


    Probabilistic model for 3D interactive segmentation

    Hershkovich, Tsachi / Shalmon, Tamar / Shitrit, Ohad et al. | British Library Online Contents | 2016


    Hierarchical probabilistic image segmentation

    Knapman, J. / Dickson, W. | British Library Online Contents | 1994


    Mixture of Trees Probabilistic Graphical Model for Video Segmentation

    Badrinarayanan, V. / Budvytis, I. / Cipolla, R. | British Library Online Contents | 2014


    Change detection by probabilistic segmentation from monocular view

    Hernandez-Lopez, F. J. / Rivera, M. | British Library Online Contents | 2014