A novel singular value decomposition-based denoising method in 4-dimensional computed tomography of the brain in stroke patients with statistical evaluation

Wonseok Yang, Jun Yong Hong, Jeong Youn Kim, Seung Ho Paik, Seung Hyun Lee, Ji Su Park, Gihyoun Lee, Beop Min Kim, Young Jin Jung

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

Computed tomography (CT) is a widely used medical imaging modality for diagnosing various diseases. Among CT techniques, 4-dimensional CT perfusion (4D-CTP) of the brain is established in most centers for diagnosing strokes and is considered the gold standard for hyperacute stroke diagnosis. However, because the detrimental effects of high radiation doses from 4DCTP may cause serious health risks in stroke survivors, our research team aimed to introduce a novel image-processing technique. Our singular value decomposition (SVD)-based image-processing technique can improve image quality, first, by separating several image components using SVD and, second, by reconstructing signal component images to remove noise, thereby improving image quality. For the demonstration in this study, 20 4D-CTP dynamic images of suspected acute stroke patients were collected. Both the images that were and were not processed via the proposed method were compared. Each acquired image was objectively evaluated using contrast-to-noise and signal-to-noise ratios. The scores of the parameters assessed for the qualitative evaluation of image quality improved to an excellent rating (p < 0.05). Therefore, our SVD-based image-denoisingtechnique improved the diagnostic value of images by improving their quality. The denoising technique and statistical evaluation can be utilized in various clinical applications to provide advanced medical services.

Original languageEnglish
Article number3063
JournalSensors (Switzerland)
Volume20
Issue number11
DOIs
Publication statusPublished - 2020 Jun 1

Bibliographical note

Funding Information:
Funding: This work was supported by Original Technology Research Program for Brain Science through the NRF (National Research Foundation of Korea) funded by Ministry of Science ICT and Future Planning (2015M3C7A1029034) and This work was supported by the BB21+ project in 2019 and This research was supported by a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI) funded by the Ministry of Health & Welfare, Republic of Korea (HI17C1501).

Funding Information:
This work was supported by Original Technology Research Program for Brain Science through the NRF (National Research Foundation of Korea) funded by Ministry of Science ICT and Future Planning (2015M3C7A1029034) and This work was supported by the BB21+ project in 2019 and This research was supported by a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI) funded by the Ministry of Health & Welfare, Republic of Korea (HI17C1501).

Publisher Copyright:
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.

Keywords

  • Acute stroke
  • Brain
  • Computed tomography
  • Contrast-to-noise
  • Gaussian noise
  • Image quality
  • Radiation doses
  • Signal-to-noise ratio
  • Singular value decomposition

ASJC Scopus subject areas

  • Analytical Chemistry
  • Information Systems
  • Instrumentation
  • Atomic and Molecular Physics, and Optics
  • Electrical and Electronic Engineering
  • Biochemistry

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