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METHODS article

Front. Nucl. Med.
Sec. Physics and Data Analysis
Volume 4 - 2024 | doi: 10.3389/fnume.2024.1505377

The effect of resizing on the natural appearance of scintigraphic images: an image similarity analysis

Provisionally accepted
  • 1 School of Electrical Engineering and Computer Science, Faculty of Engineering, University of Ottawa, Ottawa, Ontario, Canada
  • 2 Ottawa Hospital Research Institute (OHRI), Ottawa, Ontario, Canada
  • 3 Department of Physics, Faculty of Science, Carleton University, Ottawa, Ontario, Canada
  • 4 Ottawa Medical Physics Institute, Carleton University, Ottawa, Ontario, Canada
  • 5 Jubilant Radiopharma, Kirkland, Ontario, Canada
  • 6 Department of Nuclear Medicine, The Ottawa Hospital, Ottawa, Ontario, Canada

The final, formatted version of the article will be published soon.

    Background and Objective: This study aims to assess the impact of upsampling and downsampling techniques on the noise characteristics and similarity metrics of scintigraphic images in nuclear medical imaging. Methods: A physical phantom study using dynamic imaging was used to generate reproducible static images of varying count statistics. Naïve upsampling and downsampling with linear interpolation were compared against alternative methods based on the preservation of Poisson count statistics and principles of nuclear scintigraphic imaging; namely, linear interpolation with a Poisson resampling correction (upsampling) and a sliding window summation method (downsampling). For each resizing method, we computed the similarity of resized images to count-matched images acquired at the target grid size with the structural similarity index measure (SSIM) and the logarithm of the mean squared error (MSE). These image quality metrics were subsequently compared to those of two independent count-matched images at the target grid size (representing variance due to natural noise permutations) as a reference to establish an optimal resizing method. Results: Only upsampled images with the Poisson resampling correction after linear interpolation produced images that were similar to those acquired at the target grid size. For downsampling, both linear interpolation and sliding window summation yielded similar outcomes for a reduction factor of 2. However, for a reduction factor of 4, only sliding window summation resulted in image similarity metrics in agreement with those at the target grid size. Conclusions: The study underlines the importance of applying appropriate resizing techniques in nuclear medical imaging for producing realistic images at the target grid size.

    Keywords: Nuclear Medicine, Scinggraphy, image processing, Image resizing, Image noise

    Received: 02 Oct 2024; Accepted: 24 Dec 2024.

    Copyright: © 2024 Ghassel, Jabbarpour, Lang, Moulton and Klein. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Ran Klein, School of Electrical Engineering and Computer Science, Faculty of Engineering, University of Ottawa, Ottawa, Ontario, Canada

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.