In 2015 we began a sub-challenge at the EndoVis workshop at MICCAI in Munich using endoscope images of ex-vivo tissue with automatically generated annotations from robot forward kinematics and instrument CAD models. However, the limited background variation and simple motion rendered the dataset uninformative in learning about which techniques would be suitable for segmentation in real surgery. In 2017, at the same workshop in Quebec we introduced the robotic instrument segmentation dataset with 10 teams participating in the challenge to perform binary, articulating parts and type segmentation of da Vinci instruments. This challenge included realistic instrument motion and more complex porcine tissue as background and was widely addressed with modifications on U-Nets and other popular CNN architectures. In 2018 we added to the complexity by introducing a set of anatomical objects and medical devices to the segmented classes. To avoid over-complicating the challenge, we continued with porcine data which is dramatically simpler than human tissue due to the lack of fatty tissue occluding many organs.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    2018 Robotic Scene Segmentation Challenge


    Beteiligte:
    Allan, M (Autor:in) / Kondo, S (Autor:in) / Bodenstedt, S (Autor:in) / Leger, S (Autor:in) / Kadkhodamohammadi, R (Autor:in) / Luengo, I (Autor:in) / Fuentes, F (Autor:in) / Flouty, E (Autor:in) / Mohammed, A (Autor:in) / Pedersen, M (Autor:in)

    Erscheinungsdatum :

    2020-01-30


    Anmerkungen:

    ArXiv: Ithaca, NY, USA. (2020)


    Medientyp :

    Paper


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Klassifikation :

    DDC:    629



    2017 Robotic Instrument Segmentation Challenge

    Allan, M / Shvets, A / Kurmann, T et al. | BASE | 2019

    Freier Zugriff

    Scene Segmentation For Autonomous Robotic Navigation Using Sequential Laser Projected Structured Light

    Brown, C. David / Ih, Charles S. / Arce, Gonzalo R. et al. | SPIE | 1987


    Multi-Sensor Scene Segmentation

    Zhang, Xinyu / Li, Jun / Li, Zhiwei et al. | Springer Verlag | 2023


    Focus-aided scene segmentation

    Pertuz, S. / Garcia, M. A. / Puig, D. | British Library Online Contents | 2015


    RGB Road Scene Material Segmentation

    Cai, Sudong / Wakaki, Ryosuke / Nobuhara, Shohei et al. | British Library Conference Proceedings | 2023