Image-Based Scene Analysis for Computer-Assisted Laparoscopic Surgery

This thesis is concerned on image-based scene analysis for computer-assisted laparoscopic surgery. The focus lies on how to extract different types of information from laparoscopic video data. Methods for semantic analysis can be used to determine what instruments and organs are currently visible and where they are located. Quantitative analysis provides numerical information on the size and distances of structures. Workflow analysis uses information from previously seen images to estimate the progression of surgery. To demonstrate that the proposed methods function in real-world scenarios, multiple evaluations on actual laparoscopic image data recorded from surgeries were performed. The proposed methods for semantic and quantitative analysis were successfully evaluated in live phantom and animal studies and also used during a live gastric bypass on a human patient.