Combination of temporal and spatial denoising methods for cine MRI

Tsubasa Maeda; Satoshi Tamura; Satoru Hayamizu; Keigo Kawaji

doi:10.1109/LifeTech52111.2021.9391798

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 proceeding › Conference contribution

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 language	English
Title of host publication	LifeTech 2021 - 2021 IEEE 3rd Global Conference on Life Sciences and Technologies
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	44-47
Number of pages	4
ISBN (Electronic)	9781665418751
DOIs	https://doi.org/10.1109/LifeTech52111.2021.9391798
Publication status	Published - 2021 Mar 9
Externally published	Yes
Event	3rd IEEE Global Conference on Life Sciences and Technologies, LifeTech 2021 - Nara, Japan Duration: 2021 Mar 9 → 2021 Mar 11

Publication series

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

Conference

Conference	3rd IEEE Global Conference on Life Sciences and Technologies, LifeTech 2021
Country/Territory	Japan
City	Nara
Period	21/3/9 → 21/3/11

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

Access to Document

10.1109/LifeTech52111.2021.9391798

Cite this

Maeda, T., Tamura, S., Hayamizu, S., & Kawaji, K. (2021). Combination of temporal and spatial denoising methods for cine MRI. In LifeTech 2021 - 2021 IEEE 3rd Global Conference on Life Sciences and Technologies (pp. 44-47). [9391798] (LifeTech 2021 - 2021 IEEE 3rd Global Conference on Life Sciences and Technologies). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/LifeTech52111.2021.9391798

Combination of temporal and spatial denoising methods for cine MRI. / Maeda, Tsubasa; Tamura, Satoshi; Hayamizu, Satoru et al.

LifeTech 2021 - 2021 IEEE 3rd Global Conference on Life Sciences and Technologies. Institute of Electrical and Electronics Engineers Inc., 2021. p. 44-47 9391798 (LifeTech 2021 - 2021 IEEE 3rd Global Conference on Life Sciences and Technologies).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Maeda, T, Tamura, S, Hayamizu, S & Kawaji, K 2021, Combination of temporal and spatial denoising methods for cine MRI. in LifeTech 2021 - 2021 IEEE 3rd Global Conference on Life Sciences and Technologies., 9391798, LifeTech 2021 - 2021 IEEE 3rd Global Conference on Life Sciences and Technologies, Institute of Electrical and Electronics Engineers Inc., pp. 44-47, 3rd IEEE Global Conference on Life Sciences and Technologies, LifeTech 2021, Nara, Japan, 21/3/9. https://doi.org/10.1109/LifeTech52111.2021.9391798

Maeda T, Tamura S, Hayamizu S, Kawaji K. Combination of temporal and spatial denoising methods for cine MRI. In LifeTech 2021 - 2021 IEEE 3rd Global Conference on Life Sciences and Technologies. Institute of Electrical and Electronics Engineers Inc. 2021. p. 44-47. 9391798. (LifeTech 2021 - 2021 IEEE 3rd Global Conference on Life Sciences and Technologies). doi: 10.1109/LifeTech52111.2021.9391798

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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.",

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Combination of temporal and spatial denoising methods for cine MRI

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

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