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Spatial Statistics-Based Image Analysis Methods for the Study of Vascular Morphogenesis.
Guidolin, Diego; Tortorella, Cinzia; Ribatti, Domenico.
Afiliação
  • Guidolin D; Section of Anatomy, Department of Neuroscience, University of Padova Medical School, Padova, Italy. diego.guidolin@unipd.it.
  • Tortorella C; Section of Anatomy, Department of Neuroscience, University of Padova Medical School, Padova, Italy.
  • Ribatti D; Department of Basic Medical Sciences, Neurosciences and Sensory Organs, University of Bari Medical School, Bari, Italy.
Methods Mol Biol ; 2206: 67-88, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-32754812
ABSTRACT
Several studies are available addressing the mechanisms of vascular morphogenesis in order to unravel how cooperative cell behavior can follow from the underlying, genetically regulated behavior of endothelial cells and from cell-to-cell and cell-to-extracellular matrix interactions. From the morphological standpoint several aspects of the process are of interest. They include the way the pattern of vessels fills the available tissue space and how the network grows during the angiogenic process, namely how a main trunk divides into smaller branches, and how branching occurs at different distances from the root point of a vascular tree. A third morphological aspect of interest concerns the spatial relationship between vessels and tissue cells able to secrete factors modulating endothelial cells self-organization, thus influencing vascular rearrangement.In the present chapter image analysis methods allowing for a quantitative characterization of these morphological aspects will be detailed and discussed. They are almost based on concepts derived from the theoretical framework represented by spatial statistics.
Texto completo: Disponível Coleções: Bases de dados internacionais Base de dados: MEDLINE Idioma: Inglês Revista: Methods Mol Biol Assunto da revista: Biologia Molecular Ano de publicação: 2021 Tipo de documento: Artigo País de afiliação: Itália

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Texto completo: Disponível Coleções: Bases de dados internacionais Base de dados: MEDLINE Idioma: Inglês Revista: Methods Mol Biol Assunto da revista: Biologia Molecular Ano de publicação: 2021 Tipo de documento: Artigo País de afiliação: Itália