Denoising fluorescence endoscopy - A motion compensated temporal recursive video filter with an optimal minimum mean square error parameterization
Fluorescence endoscopy is an emerging technique for the detection of bladder cancer. A marker substance is brought into the patient's bladder which accumulates at cancer tissue. If a suitable narrow band light source is used for illumination, a red fluorescence of the marker substance is observable. Because of the low fluorescence photon count and because of the narrow band light source, only a small amount of light is detected by the camera's CCD sensor. This, in turn, leads to strong noise in the recorded video sequence. To overcome this problem, we apply a temporal recursive filter to the video sequence. The derivation of a filter function is presented, which leads to an optimal filter in the minimum mean square error sense. The algorithm is implemented as plug-in for the real-time capable clinical demonstrator platform RealTimeFrame and it is capable to process color videos with a resolution of 768×576 pixels at 50 frames per second.