Investigation of the effectiveness of no-reference metric in image evaluation in nuclear medicine
Shigeaki Higashiyama,
Yutaka Katayama,
Atsushi Yoshida,
Nahoko Inoue,
Takashi Yamanaga,
Takao Ichida,
Yukio Miki and
Joji Kawabe
PLOS ONE, 2024, vol. 19, issue 11, 1-23
Abstract:
Background: In nuclear medicine, normalized mean square error (NMSE) is widely used for image quality evaluation and machine adjustment. However, evaluating clinical images in nuclear medicine using NMSE necessitates acquiring a reference image, which is time consuming and impractical. Therefore, it is necessary to explore no-reference metrics, such as perception-based image quality evaluator (PIQE) and natural image quality evaluator (NIQE), as alternatives for evaluating the quality of clinical images used in nuclear medicine. Purpose: To examine whether no-reference metrics can be applied to image quality evaluations for clinical images in nuclear medicine. Methods: Images of the Hoffman Brain Phantom containing 18F–fluoro-2-deoxy-D-glucose (FDG) were obtained using Biograph Vision (Siemens Co., Ltd). From the collected images, 14 images with varying pixel counts and acquisition times were created. Sixteen images were visually evaluated by five image experts and ranked accordingly. Image quality was assessed using NMSE, PIQE, and NIQE, and rankings were calculated based on these scores. Results: The Spearman’s significance test revealed a strong correlation between image quality evaluations using PIQE and visual evaluations by specialists (p
Date: 2024
References: Add references at CitEc
Citations:
Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0310305 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 10305&type=printable (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0310305
DOI: 10.1371/journal.pone.0310305
Access Statistics for this article
More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().