Today, photodynamic diagnostics is commonly used in endoscopic intervention of the urinary bladder. Excited by a narrow band illumination, fluorescence markers enhance the visual contrast between benign and malignant tissue. Since in this modality the endoscope must be moved close to the bladder wall to provide sufficiently exposed images, the field of view (FOV) of the endoscope is very limited. This impedes the navigation and the re-identifying of multi-focal tumors for the physician. Thus, an image providing a larger FOV, composed from single images is highly desired during the intervention for surgery assistance. Since endoscopic mosaicking in real-time is still an open issue, we introduce a new feature-based image mosaicking algorithm for fluorescence endoscopy. Using a multi-threaded software design, the extraction of SURF features, the matching and the image stitching are separated in single processing threads. In an optimization step we discuss the tradeoff between feature repeatability and processing time. After adjusting an optimal thread synchronization, the optimal workload of each thread results in a fast and real-time capable computation of image mosaics. On a standard hardware platform our algorithm performs within the RealTimeFrame framework with an update rate of 8.17 frames per second at full input image resolution (780 × 576). Providing a fast A. Behrens ( ) · M. Bommes · T. Stehle · S. Gross · T. Aach growing image with an extended FOV during the intervention, the mosaic displayed on a second monitor promises high potential for surgery assistance.

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