NON PARAMETRIC CELL NUCLEI SEGMENTATION BASED ON A TRACKING OVER DEPTH FROM 3D FLUORESCENCE CONFOCAL IMAGES

Thierry Pécot 1 Shantanu Singh 2 Enrico Caserta 3 Kun Huang 4 Raghu Machiraju 5 Gustavo Leone 3
1 SERPICO - Space-timE RePresentation, Imaging and cellular dynamics of molecular COmplexes
Inria Rennes – Bretagne Atlantique
2 BROAD INSTITUTE - Broad Institute of MIT and Harvard
3 OSU - Ohio State University [Columbus]
4 Department of Biomedical Informatics [Columbus]
5 CSE - Department of Computer Science and Engineering [Columbus]
Abstract : 3D cell nuclei segmentation from fluorescence microscopy images is a key application in many biological studies. We propose a new, fully automated and non parametric method that takes advantage of the resolution anisotropy in fluorescence microscopy. The cell nuclei are first detected in 2D at each image plane and then tracked over depth through a graph based decision to recover their 3D profiles. As the tracking fails to separate very close cell nuclei along depth, we also propose a corrective step based on an intensity projection criterion. Experimental results on real data demonstrate the efficacy of the proposed method.
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Communication dans un congrès
ISBI - 9th IEEE International Symposium On Biomedical Imaging : from nano to macro - 2012, May 2012, Barcelona, Spain. 2012
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Thierry Pécot, Shantanu Singh, Enrico Caserta, Kun Huang, Raghu Machiraju, et al.. NON PARAMETRIC CELL NUCLEI SEGMENTATION BASED ON A TRACKING OVER DEPTH FROM 3D FLUORESCENCE CONFOCAL IMAGES. ISBI - 9th IEEE International Symposium On Biomedical Imaging : from nano to macro - 2012, May 2012, Barcelona, Spain. 2012. 〈hal-00921540〉

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