A Multi-threaded Mosaicking Algorithm for Fast Image Composition of Fluorescence Bladder Images

The treatment of urinary bladder cancer is usually carried out using fluorescence endoscopy. A narrow-band bluish illumination activates a tumor marker resulting in a red fluorescence. Because of low illumination power the distance between endoscope and bladder wall is kept low during the whole bladder scan, which is carried out before treatment. Thus, only a small field of view (FOV) of the operation field is provided, which impedes navigation and relocating of multi-focal tumors. Although off-line calculated panorama images can assist surgery planning, the immediate display of successively growing overview images composed from single video frames in real-time during the bladder scan, is well suited to ease navigation and reduce the risk of missing tumors. Therefore we developed an image mosaicking algorithm for fluorescence endoscopy. Due to fast computation requirements a flexible multi-threaded software architecture based on our RealTimeFrame platform is developed. Different algorithm tasks, like image feature extraction, matching and stitching are separated and applied by independent processing threads. Thus, different implementation of single tasks can be easily evaluated. In an optimization step we evaluate the trade-off between feature repeatability and total processing time, consider the thread synchronization, and achieve a constant workload of each thread. Thus, a fast computation of panoramic images is performed on a standard hardware platform, preserving full input image resolution (780x576) at the same time. Displayed on a second clinical monitor, the extended FOV of the image composition promises high potential for surgery assistance.