Deblurring Multispectral Laparoscopic Images

  • Geoffrey Jones
  • Neil Clancy
  • Simon Arridge
  • Dan Elson
  • Danail Stoyanov
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8498)


Multispectral imaging is an optical modality that can provide real-time in vivo information about tissue characteristics and function through signal sensitivity to chromophores in the tissue. In this paper, we present a deblurring strategy that enables imaging of dynamic tissues at wavelengths where the required acquisition time can cause significant motion blur and obscure the image. We use deconvolution for spatially varying kernels to process multispectral information obtained by using a novel laparoscopic imaging device. The trinocular design of the system allows visible light images provide information about the tissue morphology and motion that we use to construct a per pixel deformation map. We demonstrate that with the proposed method the multispectral image stack can be synthesised into a meaningful signal even in the presence of significant tissue motion. Experiments on synthetic data validate the numerical properties of the method and experiments with ex vivo tissue demonstrate the practical potential of the technique.


Non-rigid Deblurring Multispectral Imaging Surgical Imaging Surgical Vision 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Geoffrey Jones
    • 1
  • Neil Clancy
    • 2
    • 3
  • Simon Arridge
    • 1
  • Dan Elson
    • 2
    • 3
  • Danail Stoyanov
    • 1
  1. 1.Centre for Medical Image Computing, Department of Computer ScienceUniversity College LondonUK
  2. 2.Hamlyn Centre for Robotic Surgery, Institute of Global Health InnovationImperial College LondonUK
  3. 3.Department of Surgery and CancerImperial College LondonUK

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