Cell viability assessment via deep learning solutions

Information

• Publication Type: Master Thesis
• Workgroup(s)/Project(s): not specified
• Date: 2026
• TU Wien Library: AC18101029
• Second Supervisor: Renata Georgia Raidou
• Open Access: yes
• First Supervisor: Eduard Gröller
• Pages: 107
• Keywords: cell viability, segmentation, ground-truth data

Abstract

Additional Files and Images

Weblinks

• Entry in reposiTUm (TU Wien Publication Database)
• CatalogPlus (TU Wien Library)
• DOI: 10.34726/hss.2026.142887

BibTeX

@mastersthesis{bront-2026-cva,
  title =      "Cell viability assessment via deep learning solutions",
  author =     "Mark-Christian Bront",
  year =       "2026",
  pages =      "107",
  address =    "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria",
  school =     "Research Unit of Computer Graphics, Institute of Visual
               Computing and Human-Centered Technology, Faculty of
               Informatics, TU Wien",
  keywords =   "cell viability, segmentation, ground-truth data",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2026/bront-2026-cva/",
}