Toward effective noise reduction for sub-Nyquist high-frame-rate MRI techniques with deep learning

Yudai Suzuki*, Keigo Kawaji, Amit R. Patel, Satoshi Tamura, Satoru Hayamizu

*Corresponding author for this work

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

1 Citation (Scopus)

Abstract

Cine Cardiac Magnetic Resonance (Cine-CMR) is one example of dynamic MRI approaches to image organs that exhibit periodic motion. Conventional routine clinical Cine-CMR are typically obtained at 20-35 frames per second (fps) with temporal window sizes of 40-50 milliseconds. We have recently shown the feasibility of significantly increasing this overall frame rate by an acquisition of MRI k-space using a highly optimized radial sampling pattern with respect to both spatial and temporal coverage. In brief, our proposed approach acquires a significantly undersampled radial MRI k-space while encoding spatially and temporally periodic noise characteristics through the undersampled radial MRI acquisition; however, remnant radial streaking noise remain under physiologic imaging conditions. In this research, we propose to further remove these streaking noise, employing a Spatio-Temporal Denoising Auto-Encoder (ST-DAE) based on deep learning. We evaluate performance of our method in addressing such remnant artifact using ST-DAE; PSNR is used to evaluate image quality, and computational time is also discussed.

Original languageEnglish
Title of host publicationProceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1136-1139
Number of pages4
ISBN (Electronic)9781538615423
DOIs
Publication statusPublished - 2018 Feb 5
Externally publishedYes
Event9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017 - Kuala Lumpur, Malaysia
Duration: 2017 Dec 122017 Dec 15

Publication series

NameProceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017
Volume2018-February

Other

Other9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017
Country/TerritoryMalaysia
CityKuala Lumpur
Period17/12/1217/12/15

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Information Systems
  • Signal Processing

Fingerprint

Dive into the research topics of 'Toward effective noise reduction for sub-Nyquist high-frame-rate MRI techniques with deep learning'. Together they form a unique fingerprint.

Cite this