Publikation: Frame-Based Classification of Operation...
Stammdaten
Titel: | Frame-Based Classification of Operation Phases in Cataract Surgery Videos |
Untertitel: | |
Kurzfassung: | Cataract surgeries are frequently performed to correct a lens opacification of the human eye, which usually appears in the course of aging. These surgeries are conducted with the help of a microscope and are typically recorded on video for later inspection and educational purposes. However, post-hoc visual analysis of video recordings is cumbersome and time-consuming for surgeons if there is no navigation support, such as bookmarks to specific operation phases. To prepare the way for an automatic detection of operation phases in cataract surgery videos, we investigate the effectiveness of a deep convolutional neural network (CNN) to automatically assign video frames to operation phases, which can be regarded as a single-label multi-class classification problem. In absence of public datasets of cataract surgery videos, we provide a dataset of 21 videos of standardized cataract surgeries and use it to train and evaluate our CNN classifier. Experimental results display a mean F1-score of about 68% for frame-based operation phase classification, which can be further improved to 75% when considering temporal information of video frames in the CNN architecture. |
Schlagworte: |
Publikationstyp: | Beitrag in Sammelwerk (Autorenschaft) |
Erscheinungsdatum: | 01.2018 (Print) |
Erschienen in: |
MultiMedia Modeling - 24th International Conference, MMM 2018 (Part 1)
MultiMedia Modeling - 24th International Conference, MMM 2018 (Part 1)
(2018)
(
Springer;
K. Schöffmann, T. Chalidabhongse, C. Ngo, N. O´Connor, S. Aramvith, Y. Ho, M. Gabbouj, A. Elgammal
)
K. Schöffmann, T. Chalidabhongse, C. Ngo, N. O´Connor, S. Aramvith, Y. Ho, M. Gabbouj, A. Elgammal
|
Titel der Serie: | LNCS |
Bandnummer: | 10704 |
Erstveröffentlichung: | Ja |
Version: | - |
Seite: | S. 241 - 253 |
Bild der Titelseite: |
Versionen
Keine Version vorhanden |
Erscheinungsdatum: | |
ISBN (e-book): | - |
eISSN: | - |
DOI: | http://dx.doi.org/10.1007/978-3-319-73603-7_20 |
Homepage: | - |
Open Access |
|
Erscheinungsdatum: | 01.2018 |
ISBN: |
|
ISSN: | 0302-9743 |
Homepage: | https://link.springer.com/chapter/10.1007/978-3-319-73603-7_20 |
AutorInnen
Manfred Jürgen Primus (intern) | ||||
Doris Putzgruber-Adamitsch
|
||||
Mario Taschwer (intern) | ||||
Bernd Münzer (intern) | ||||
Yosuf El-Shabrawi
|
||||
Laszlo Böszörmenyi (intern) | ||||
Klaus Schöffmann (intern) |
Zuordnung
Organisation | Adresse | ||||
---|---|---|---|---|---|
Fakultät für Technische Wissenschaften
Institut für Informationstechnologie
|
AT - 9020 Klagenfurt am Wörthersee |
Kategorisierung
Sachgebiete | |
Forschungscluster | Kein Forschungscluster ausgewählt |
Peer Reviewed |
|
Publikationsfokus |
Klassifikationsraster der zugeordneten Organisationseinheiten:
|
Arbeitsgruppen |
|
Kooperationen
Organisation | Adresse | ||||
---|---|---|---|---|---|
KABEG Klinikum Klagenfurt
|
AT - 9020 Klagenfurt |
Forschungsaktivitäten
(Achtung: Externe Aktivitäten werden im Suchergebnis nicht mitangezeigt)
Projekte: |
|
Publikationen: | Keine verknüpften Publikationen vorhanden |
Veranstaltungen: |
|
Vorträge: |
|