Abstract
Cystoscopic video can be cumbersome to review; however, preservation of data in the form of 3D bladder reconstructions has the potential to improve patient care. Unfortunately, not all cystoscopy videos produce viable reconstructions, because their underlying frames contain artifacts such as motion blur and bladder debris, which consequently make them unusable for 3D reconstructions. Here, we develop a real-time pipeline, termed the Assessment and Feedback Pipeline (AFP), that alerts clinicians when unusable frames are detected and encourages them to recollect the last few seconds of data. We show that the AFP classifies frames as usable or unusable with a balanced accuracy of 81.60% and demonstrate that use of the AFP improves 3D reconstruction coverage. These results suggest that clinical implementation of the AFP would improve 3D reconstruction quality through real-time detection and recollection of unusable frames.