Hierarchical graph representations in digital pathology

Volume: 75, Pages: 102264 - 102264
Published: Jan 1, 2022
Abstract
Cancer diagnosis, prognosis, and therapy response predictions from tissue specimens highly depend on the phenotype and topological distribution of constituting histological entities. Thus, adequate tissue representations for encoding histological entities is imperative for computer aided cancer patient care. To this end, several approaches have leveraged cell-graphs, capturing the cell-microenvironment, to depict the tissue. These allow for...
Paper Details
Title
Hierarchical graph representations in digital pathology
Published Date
Jan 1, 2022
Volume
75
Pages
102264 - 102264
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.