Denoising fluorescence endoscopy: a motion compensated temporal recursive video filter with an optimal minimum mean square error parameterization

  • Authors:

  • Thomas Stehle;Jonas Wulff;Alexander Behrens;Sebastian Gross;Til Aach

  • Affiliations:

  • Institute of Imaging & Computer Vision, RWTH Aachen University, Aachen, Germany;Institute of Imaging & Computer Vision, RWTH Aachen University, Aachen, Germany;Institute of Imaging & Computer Vision, RWTH Aachen University, Aachen, Germany;Institute of Imaging & Computer Vision, RWTH Aachen University, Aachen, Germany;Institute of Imaging & Computer Vision, RWTH Aachen University, Aachen, Germany

  • Venue:
  • ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
  • Year:
  • 2009

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Abstract

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.