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Discrimination of Complex Activation Patterns in Near Infrared Optical Tomography with Artificial Neural Networks

  • Jingjing Jiang
  • Linda Ahnen
  • Scott Lindner
  • Aldo Di Costanzo Mata
  • Alexander Kalyanov
  • Felix Scholkmann
  • Martin Wolf
  • Salvador Sánchez Majos
Chapter
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 1072)

Abstract

Near-infrared optical tomography (NIROT) has great promise for many clinical problems. Here we focus on the study of brain function. During NIROT image reconstruction of brain activity, an inverse problem has to be solved that is sensitive to small superficial perturbations on the head such as e.g. birthmarks on the skin and hair. To consider these perturbations, standard physical modeling is unpractical, since it requires the implementation of detailed information that is generally unavailable. The aim here was to test whether artificial neural networks (ANN) are able to handle such perturbations and thus detect brain activity correctly. For simplicity, we created a virtual test model, where we simulated a pattern of activated and resting brain regions, which was covered by skin features like hair or melanin. We compared the performance of this ANN approach with that of an inverse problem based on a Monte Carlo (MC) model for light propagation. We conclude that ANNs tolerate substantially higher levels of skin perturbations than MC models and consequently are more suitable for detecting brain activity.

Notes

Acknowledgments

This work was supported by Swiss Cancer Research grant KFS-3732-08-2015, the SwissTransMed project ONIRIUS and the Clinical Research Priority Programs (CRPP) Tumor Oxygenation TO2 and Molecular Imaging Network Zurich MINZ of University of Zurich.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Jingjing Jiang
    • 1
  • Linda Ahnen
    • 1
  • Scott Lindner
    • 1
  • Aldo Di Costanzo Mata
    • 1
  • Alexander Kalyanov
    • 1
  • Felix Scholkmann
    • 1
  • Martin Wolf
    • 1
  • Salvador Sánchez Majos
    • 1
  1. 1.Biomedical Optics Research Laboratory (BORL), Department of NeonatologyUniversity Hospital Zurich (USZ)ZurichSwitzerland

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