Combination of temporal and spatial denoising methods for cine MRI

Tsubasa Maeda, Satoshi Tamura, Satoru Hayamizu, Keigo Kawaji

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In this paper, we propose a denoising method for cine MRI acquired by MoPS. The MoPS-based cine MRI has a high FPS but contains reconstruction noise. DISPEL, a conventional method, performs denoising in the temporal domain. A neural network is further introduced to remove spatial noise. Different from most those methods requiring noisy and clean images, we choose an unsupervised scheme, N2N. We combine these two methods to perform temporal and spatial denoising for cine MRI. Experimental results show that the proposed method is able to remove noise from cine MRIs acquired by MoPS without removing tissue signal.

Original languageEnglish
Title of host publicationLifeTech 2021 - 2021 IEEE 3rd Global Conference on Life Sciences and Technologies
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages44-47
Number of pages4
ISBN (Electronic)9781665418751
DOIs
Publication statusPublished - 2021 Mar 9
Externally publishedYes
Event3rd IEEE Global Conference on Life Sciences and Technologies, LifeTech 2021 - Nara, Japan
Duration: 2021 Mar 92021 Mar 11

Publication series

NameLifeTech 2021 - 2021 IEEE 3rd Global Conference on Life Sciences and Technologies

Conference

Conference3rd IEEE Global Conference on Life Sciences and Technologies, LifeTech 2021
Country/TerritoryJapan
CityNara
Period21/3/921/3/11

Keywords

  • Cine MRI
  • Image denoising
  • Neural network
  • Signal processing
  • Unsupervised learning

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health(social science)
  • Biochemistry
  • Artificial Intelligence
  • Computer Science Applications

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