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Abstract

Dynamic Positron Emission Tomography (dPET) images are inherently affected by noise and low spatial resolution. The problems aforementioned may lead to incorrect estimation of the uptake of the tracer in tissues. In this work, we present a novel method for enhancing the signal-to-noise ratio of dPET images. The method consist in a edge preserving filter based upon an indirect image. The indirect image give orientation to the treatment so as to process all frames at the same fashion. We exploit the spatial and temporal information along the entire sequence in order to adapt the filtering process to preserve edges between functional regions. Comparative experimentations on realistic simulations validate the potential of the proposed method.

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Information & Authors

Information

Published in

ISBN: 978-1-78561-887-1

History

Published in print: 2018
Published online: 21 May 2024

Inspec keywords

  1. computer vision
  2. image classification
  3. image segmentation
  4. medical image processing
  5. object detection

Keywords

  1. image denoising
  2. positron emission tomography
  3. neural nets
  4. feature extraction
  5. text analysis
  6. computer vision
  7. image segmentation
  8. object detection
  9. image classification
  10. medical image processing

Subjects

  1. Conference proceedings
  2. Patient diagnostic methods and instrumentation
  3. General electrical engineering topics
  4. Image recognition
  5. Optical, image and video signal processing
  6. General and management topics
  7. Biology and medical computing
  8. Computer vision and image processing techniques

Inspec keywords

  1. image denoising
  2. image filtering
  3. medical image processing
  4. positron emission tomography

Keywords

  1. Dynamic Positron Emission Tomography images
  2. signal-to-noise ratio
  3. dPET images
  4. edge preserving filter
  5. indirect image
  6. spatial information
  7. temporal information
  8. filtering process
  9. dynamic PET image denoising
  10. spatial resolution
  11. functional regions

Authors

Affiliations

P. Gonzalez
DCI, Univ. Catolica del Maule, TalcaChile
B. Alcaino
DCI, Univ. Catolica del Maule, TalcaChile
R. Barrientos
DCI, Univ. Catolica del Maule, TalcaChile
M. Mora
DCI, Univ. Catolica del Maule, TalcaChile
F. Tirado
DCI, Univ. Catolica del Maule, TalcaChile
C. Tauber
UMRS INSERM, Univ. Francois Rabelais, ToursFrance

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9th International Conference on Pattern Recognition Systems (ICPRS 2018)
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Dynamic PET image denoising

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