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Image-Based Scene Analysis for Computer-Assisted Laparoscopic Surgery

Bodenstedt, Sebastian

Abstract (englisch):
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.

Volltext §
DOI: 10.5445/IR/1000084137
Veröffentlicht am 06.07.2018
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Publikationstyp Hochschulschrift
Publikationsjahr 2018
Sprache Englisch
Identifikator urn:nbn:de:swb:90-841376
KITopen-ID: 1000084137
Verlag Karlsruher Institut für Technologie (KIT)
Umfang X, 143 S.
Art der Arbeit Dissertation
Fakultät Fakultät für Informatik (INFORMATIK)
Institut Institut für Anthropomatik und Robotik (IAR)
Prüfungsdatum 17.07.2017
Referent/Betreuer Prof. R. Dillmann
Projektinformation GRK 1126/2 (DFG, DFG KOORD, GRK 1126/2)
TRR 125/1 (DFG, DFG KOORD, TRR 125/1 2012)
TRR 125/2 (DFG, DFG KOORD, TRR 125/2 2016)
Schlagwörter Computer assisted surgery, context-awareness, laparoscopy, surgical image analysis
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