Gap detection in endoscopic video sequences using graphs.

In minimal invasive surgery (MIS) a complete and seamless inspection of organs, e.g. the urinary bladder, using video endoscopes is often required for diagnostics. Since the endoscope is usually guided by free-hand, it is difficult to ensure a sequence of seamless frame transitions. Also 2-D panoramic images showing an extended field of view (FOV) do not provide always reliable results, since their interpretations are limited by potentially strong geometric distortions. To overcome these limitations and provide a direct verification method, we develop a gap detection algorithm using graphs. Exploiting the motion information of the applied zig-zag scan, we construct a graph representation of the video sequence. Without any explicit global image visualization our graph search algorithm identifies reliably frame discontinuities, which would lead to holes and slit artifacts in a panoramic view. The algorithm shows high detection rates and provides a fast method to verify frame discontinuities in the whole video sequence. Missed regions are highlighted by local image compositions which can be displayed during the intervention for assistance and inspection control.