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Structural Similarity Based Anatomical and Functional Brain Imaging Fusion

  • Nishant KumarEmail author
  • Nico Hoffmann
  • Martin Oelschlägel
  • Edmund Koch
  • Matthias Kirsch
  • Stefan Gumhold
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11846)

Abstract

Multimodal medical image fusion helps in combining contrasting features from two or more input imaging modalities to represent fused information in a single image. One of the pivotal clinical applications of medical image fusion is the merging of anatomical and functional modalities for fast diagnosis of malign tissues. In this paper, we present a novel end-to-end unsupervised learning based Convolutional neural network (CNN) for fusing the high and low frequency components of MRI-PET grayscale image pairs publicly available at ADNI by exploiting Structural Similarity Index (SSIM) as the loss function during training. We then apply color coding for the visualization of the fused image by quantifying the contribution of each input image in terms of the partial derivatives of the fused image. We find that our fusion and visualization approach results in better visual perception of the fused image, while also comparing favorably to previous methods when applying various quantitative assessment metrics.

Keywords

Medical image fusion MRI-PET Convolutional neural networks (CNN) Structural similarity index (SSIM) 

Notes

Acknowledgements

This work was supported by the European Social Fund (project no. 100312752) and the Saxonian Ministry of Science and Art.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Nishant Kumar
    • 1
    Email author
  • Nico Hoffmann
    • 2
  • Martin Oelschlägel
    • 3
  • Edmund Koch
    • 3
  • Matthias Kirsch
    • 4
  • Stefan Gumhold
    • 1
  1. 1.Computer Graphics and VisualisationTechnische Universität DresdenDresdenGermany
  2. 2.Institute of Radiation PhysicsHelmholtz-Zentrum Dresden-RossendorfDresdenGermany
  3. 3.Clinical Sensoring and MonitoringTechnische Universität DresdenDresdenGermany
  4. 4.Department of NeurosurgeryUniversity Hospital Carl Gustav CarusDresdenGermany

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