Stammdaten

Relevance Detection of Ophthalmic Surgery Videos (OVID)
Beschreibung:

In an interdisciplinary research project, computer scientists and physicians collaborate to develop and evaluate methods for automatic detection of relevant temporal segments in ophthalmic surgery 1 videos (OSVs). The main objective is the creation of relevance models allowing to detect video segments that are relevant for educational, scientific, or documentary purposes in medicine. Relevance models are produced by machine learning algorithms, which are trained using OSVs that were annotated by surgeons. Important instances of relevant OSV segments are irregular operation (OP) phases, which deviate from the usual procedure used in quasi-standardized ophthalmic surgeries. The automatic detection and classification of irregularities that occur more frequently and hence allow training of machine learning algorithms, provide an additional benefit for the creation of OSV datasets targeted at medical education or research. The development and evaluation of automatic classifiers of irregularities therefore represents another research objective of this project. Relevance models can be used to compress and store OSVs efficiently. This project will develop and evaluate appropriate methods and algorithms to achieve this goal. Finally, we want to demonstrate that relevant OSV segments are useful for medical research by addressing three specific medical research questions related to a certain type of ophthalmic surgery (cataract) using video analysis.

Schlagworte: Multimedia, Video content analysis, Machine learning, Biomedical engineering, Surgery videos, Computer vision
Kurztitel: OVID
Zeitraum: 01.10.2018 - 31.03.2023
Kontakt-Email: ks@itec.aau.at
Homepage: http://ovid.itec.aau.at/

MitarbeiterInnen

MitarbeiterInnen Funktion Zeitraum
Klaus Schöffmann (intern)
  • Projektleiter/in
  • 01.10.2018 - 31.03.2023
Mario Taschwer (intern)
  • Projektleiter/in
  • 01.10.2018 - 31.03.2023
Natalia Mathá (intern)
  • wiss. Mitarbeiter/in
  • 01.10.2018 - 30.11.2021
Markus Fox (intern)
  • stud. Mitarbeiter/in
  • 01.10.2018 - 31.12.2020
Negin Ghamsarian (intern)
  • wiss. Mitarbeiter/in
  • 01.06.2019 - 30.11.2021
Andreas Leibetseder (intern)
  • wiss. Mitarbeiter/in
  • 01.11.2020 - 31.07.2021
Lisa Christina Bürger (intern)
  • stud. Mitarbeiter/in
  • stud. Mitarbeiter/in
  • 05.08.2019 - 05.02.2020
  • 14.09.2020 - 31.07.2021
Daniela Stefanics (intern)
  • stud. Mitarbeiter/in
  • 01.10.2021 - 31.05.2022

Kategorisierung

Projekttyp Forschungsförderung (auf Antrag oder Ausschreibung)
Förderungstyp §26
Forschungstyp
  • Grundlagenforschung
Sachgebiete
  • 102020 - Medizinische Informatik (305905)
Forschungscluster Kein Forschungscluster ausgewählt
Genderrelevanz Genderrelevanz nicht ausgewählt
Projektfokus
  • Science to Science (Qualitätsindikator: I)
Klassifikationsraster der zugeordneten Organisationseinheiten:
Arbeitsgruppen
  • Distributed Multimedia Systems

Kooperationen

Organisation Adresse
KABEG Klinikum Klagenfurt
Feschnigstraße 11
9020 Klagenfurt
Österreich - Kärnten
http://www.klinikum-klagenfurt.at/
Feschnigstraße 11
AT - 9020  Klagenfurt