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Tracking cells in the brain of small animals using synchrotron multi-spectral phase contrast imaging

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  • Additional Information
    • Contributors:
      Cardiovasculaire, métabolisme, diabétologie et nutrition (CarMeN); Université Claude Bernard Lyon 1 (UCBL); Université de Lyon-Université de Lyon-Hospices Civils de Lyon (HCL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE); Pennsylvania State University (Penn State); Penn State System; Synchrotron Radiation for Biomedicine = Rayonnement SynchroTROn pour la Recherche BiomédicalE (STROBE); Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Grenoble Alpes (UGA); ANR-18-CE19-0003,BREAKTHRU,Développement de l'imagerie bicolore à l'aide d'un scanner X spectral à comptage de photons pour l'évaluation in-vivo de thérapies cellulaires(2018)
    • Publication Information:
      CCSD
      SPIE
    • Publication Date:
      2021
    • Collection:
      Hospices Civils de Lyon (HCL): HAL
    • Subject Terms:
    • Abstract:
      International audience ; Synchrotron X-ray multi-spectral imaging is a novel imaging modality that may allow tracking cells at high resolution in small animal models. The data volume generated by such technique can be of hundreds of Gigabytes for one animal Automatic, robust and rapid pipeline is therefore of paramount importance for large-scale studies. The goal of this article is to present a full image analysis pipeline ranging from the CT reconstruction up to the segmentation of nanoparticles - labeled-cells. Experimentally, rats that had received an intracerebral transplantation of gold nanoparticles-labeled cells were imaged in vivo in phase contrast mode (propagation based-imaging technique) at two different energies strategically chosen around the k-edge of gold. We apply a dedicated phase retrieval technique on each projection (out of 2000 for complete 2 pi rotation) before CT reconstruction. Then, a rigid registration is performed between the images below and above k-edge for accurate subtraction of the two data sets, leading to gold concentration maps. Due to the large number of specimens, the registration is based on the automatic segmentation of the cranial skull. Finally, an automatic segmentation of gold-labeled cells within the brain is performed based on high spots of gold concentrations. An example of an in-vivo data set for stroke cell therapy is presented.
    • Relation:
      WOS: 000672731900152
    • Accession Number:
      10.1117/12.2580841
    • Online Access:
      https://hal.science/hal-03428586
      https://hal.science/hal-03428586v1/document
      https://hal.science/hal-03428586v1/file/spie_article.pdf
      https://doi.org/10.1117/12.2580841
    • Rights:
      info:eu-repo/semantics/OpenAccess
    • Accession Number:
      edsbas.DF46186A