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Computer Science - Research and Development

, Volume 26, Issue 1–2, pp 125–134 | Cite as

A non-linear multi-scale blending algorithm for fluorescence bladder images

  • Alexander BehrensEmail author
  • Martin Guski
  • Thomas Stehle
  • Sebastian Gross
  • Til Aach
Special Issue Paper

Abstract

The composition of panoramic images of the internal urinary bladder wall from single endoscope images can strongly support the off-line documentation and surgery planning for cancer treatment, as well as assist the re-identification of multi-focal tumors during a cystoscopy. Unlike white light endoscopy, fluorescence techniques such as photodynamic diagnostics (PDD) lower the risk of missing flat and small tumors due to an enhanced tissue contrast. As a result of the low illumination power and the free hand movement of the endoscope, PDD video sequences usually show strong variations in illumination and resolution. During the subsequent mosaicking and blending process, these effects impede the preservation of original and unbiased input image information in the composed panoramic overview image, and make it difficult to avoid visual interpolation artifacts. Thus, a non-linear intensity based multi-scale blending method for fluorescence images is developed. Based on a highest intensity decision, a region mask modeling the endoscopic illumination characteristic is used to weight the input images on several sub-bands of a Laplacian pyramid. In comparison to basic linear interpolation and standard multi-scale methods the new method preserves high fluorescence intensities as well as fine vessel structures in the final image composition. Furthermore the adaptive characteristics of the blending algorithm allow the physician to move the endoscope more freely along the bladder wall during the image mosaicking process.

Keywords

Blending Interpolation Image mosaicking Panorama Fluorescence endoscopy Bladder cancer 

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Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Alexander Behrens
    • 1
    Email author
  • Martin Guski
    • 1
  • Thomas Stehle
    • 1
  • Sebastian Gross
    • 1
  • Til Aach
    • 1
  1. 1.Institute of Imaging & Computer VisionRWTH Aachen UniversityAachenGermany

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