Content-based retrieval in videos from laparoscopic surgery

Klaus Schoeffmann; Christian Beecks; Mathias Lux; Merih Seran Uysal; Thomas Seidl

doi:10.1117/12.2216864

18 March 2016 Content-based retrieval in videos from laparoscopic surgery

Klaus Schoeffmann, Christian Beecks, Mathias Lux, Merih Seran Uysal, Thomas Seidl

Proceedings Volume 9786, Medical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling; 97861V (2016) https://doi.org/10.1117/12.2216864
Event: SPIE Medical Imaging, 2016, San Diego, California, United States

Abstract

In the field of medical endoscopy more and more surgeons are changing over to record and store videos of their endoscopic procedures for long-term archival. These endoscopic videos are a good source of information for explanations to patients and follow-up operations. As the endoscope is the "eye of the surgeon", the video shows the same information the surgeon has seen during the operation, and can describe the situation inside the patient much more precisely than an operation report would do. Recorded endoscopic videos can also be used for training young surgeons and in some countries the long-term archival of video recordings from endoscopic procedures is even enforced by law. A major challenge, however, is to efficiently access these very large video archives for later purposes. One problem, for example, is to locate specific images in the videos that show important situations, which are additionally captured as static images during the procedure. This work addresses this problem and focuses on contentbased video retrieval in data from laparoscopic surgery. We propose to use feature signatures, which can appropriately and concisely describe the content of laparoscopic images, and show that by using this content descriptor with an appropriate metric, we are able to efficiently perform content-based retrieval in laparoscopic videos. In a dataset with 600 captured static images from 33 hours recordings, we are able to find the correct video segment for more than 88% of these images.

Citation Download Citation

Klaus Schoeffmann, Christian Beecks, Mathias Lux, Merih Seran Uysal, and Thomas Seidl "Content-based retrieval in videos from laparoscopic surgery", Proc. SPIE 9786, Medical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling, 97861V (18 March 2016); https://doi.org/10.1117/12.2216864

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