Instrument classification in laparoscopic videos

In medical endoscopy more and more surgeons record videos of their interventions in a long-term storage archive for later retrieval. In order to allow content-based search in such endoscopic video archives, the video data needs to be indexed first. However, even the very basic step of content-based indexing, namely content segmentation, is already very challenging due to the special characteristics of such video data. Therefore, we propose to use instrument classification to enable semantic segmentation of laparoscopic videos. In this paper, we evaluate the performance of such an instrument classification approach. Our results show satisfying performance for all instruments used in our evaluation.