Comparative study of image registration techniques for bladder video-endoscopy
This work tackles the problem of visualizing widespread lesions in bladder cancer diagnosis for clinicians, but it is incremental as it compares existing techniques.
The study compared two mosaicing algorithms for constructing panoramic maps of bladder walls from video-endoscopy images to address the limitation of small imaged areas, finding performance assessed on real and simulated data.
Bladder cancer is widely spread in the world. Many adequate diagnosis techniques exist. Video-endoscopy remains the standard clinical procedure for visual exploration of the bladder internal surface. However, video-endoscopy presents the limit that the imaged area for each image is about nearly 1cm2. And, lesions are, typically, spread over several images. The aim of this contribution is to assess the performance of two mosaicing algorithms leading to the construction of panoramic maps (one unique image) of bladder walls. The quantitative comparison study is performed on a set of real endoscopic exam data and on simulated data relative to bladder phantom.