Magnetic resonance fingerprinting using recurrent neural networks

Ilkay Oksuz; Gastao Cruz; James Clough; Aurelien Bustin; Nicolo Fuin; Rene M. Botnar; Claudia Prieto; Andrew P. King; Julia A. Schnabel

doi:10.1109/ISBI.2019.8759502

Magnetic resonance fingerprinting using recurrent neural networks

Ilkay Oksuz
, Gastao Cruz
, James Clough
, Aurelien Bustin
, Nicolo Fuin
, Rene M. Botnar
, Claudia Prieto
, Andrew P. King
, Julia A. Schnabel

King's College London

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

36 Atıf (Scopus)

Özet

Magnetic Resonance Fingerprinting (MRF) is a new approach to quantitative magnetic resonance imaging that allows simultaneous measurement of multiple tissue properties in a single, time-efficient acquisition. Standard MRF reconstructs parametric maps using dictionary matching and requires high computational time. We propose to perform MRF map reconstruction using a recurrent neural network, which exploits the time-dependent information of the MRF signal evolution. We evaluate our method on multiparametric synthetic signals and compare it to existing MRF map reconstruction approaches, including those based on neural networks. Our method achieves state-of-the-art estimates of T1 and T2 values. In addition, the reconstruction time is reduced compared to dictionary-matching based approach.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging
Yayınlayan	IEEE Computer Society
Sayfalar	1537-1540
Sayfa sayısı	4
ISBN (Elektronik)	9781538636411
DOI'lar	https://doi.org/10.1109/ISBI.2019.8759502
Yayın durumu	Yayınlandı - Nis 2019
Harici olarak yayınlandı	Evet
Etkinlik	16th IEEE International Symposium on Biomedical Imaging, ISBI 2019 - Venice, Italy Süre: 8 Nis 2019 → 11 Nis 2019

Yayın serisi

Adı	Proceedings - International Symposium on Biomedical Imaging
Hacim	2019-April
ISSN (Basılı)	1945-7928
ISSN (Elektronik)	1945-8452

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	16th IEEE International Symposium on Biomedical Imaging, ISBI 2019
Ülke/Bölge	Italy
Şehir	Venice
Periyot	8/04/19 → 11/04/19

Bibliyografik not

Publisher Copyright:
© 2019 IEEE.

Finansman

This work was supported by an EPSRC programme Grant (EP/P001009/1) and the Wellcome EPSRC Centre for Medical Engineering at School of Biomedical Engineering and Imaging Sciences, Kings College London (WT 203148/Z/16/Z). We acknowledge financial support from the Department of Health via the NIHR comprehensive Biomedical Research Centre award to Guys & St Thomas NHS Foundation Trust with KCL and Kings College Hospital NHS Foundation Trust. ∗ Joint last authors.

Finansörler	Finansör numarası
Wellcome EPSRC Centre for Medical Engineering at School of Biomedical Engineering and Imaging Sciences, Kings College London	WT 203148/Z/16/Z
King's College Hospital NHS Foundation Trust
NIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer Research
Engineering and Physical Sciences Research Council	EP/P001009/1, EP/N026993/1, EP/M000133/1
National Institute for Health Research
Department of Health and Social Care

Belgeye Erişim

10.1109/ISBI.2019.8759502

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Oksuz, I., Cruz, G., Clough, J., Bustin, A., Fuin, N., Botnar, R. M., Prieto, C., King, A. P., & Schnabel, J. A. (2019). Magnetic resonance fingerprinting using recurrent neural networks. In ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging (pp. 1537-1540). Makale 8759502 (Proceedings - International Symposium on Biomedical Imaging; Hac. 2019-April). IEEE Computer Society. https://doi.org/10.1109/ISBI.2019.8759502

@inproceedings{fa1aea85a21c4294b8400153a959c0c3,

title = "Magnetic resonance fingerprinting using recurrent neural networks",

abstract = "Magnetic Resonance Fingerprinting (MRF) is a new approach to quantitative magnetic resonance imaging that allows simultaneous measurement of multiple tissue properties in a single, time-efficient acquisition. Standard MRF reconstructs parametric maps using dictionary matching and requires high computational time. We propose to perform MRF map reconstruction using a recurrent neural network, which exploits the time-dependent information of the MRF signal evolution. We evaluate our method on multiparametric synthetic signals and compare it to existing MRF map reconstruction approaches, including those based on neural networks. Our method achieves state-of-the-art estimates of T1 and T2 values. In addition, the reconstruction time is reduced compared to dictionary-matching based approach.",

keywords = "Gru, Lstm, Magnetic resonance fingerprinting, Parameter mapping, Recurrent neural networks",

author = "Ilkay Oksuz and Gastao Cruz and James Clough and Aurelien Bustin and Nicolo Fuin and Botnar, \{Rene M.\} and Claudia Prieto and King, \{Andrew P.\} and Schnabel, \{Julia A.\}",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 16th IEEE International Symposium on Biomedical Imaging, ISBI 2019 ; Conference date: 08-04-2019 Through 11-04-2019",

year = "2019",

month = apr,

doi = "10.1109/ISBI.2019.8759502",

language = "English",

series = "Proceedings - International Symposium on Biomedical Imaging",

publisher = "IEEE Computer Society",

pages = "1537--1540",

booktitle = "ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging",

address = "United States",

}

Oksuz, I, Cruz, G, Clough, J, Bustin, A, Fuin, N, Botnar, RM, Prieto, C, King, AP & Schnabel, JA 2019, Magnetic resonance fingerprinting using recurrent neural networks. in ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging., 8759502, Proceedings - International Symposium on Biomedical Imaging, hac. 2019-April, IEEE Computer Society, pp. 1537-1540, 16th IEEE International Symposium on Biomedical Imaging, ISBI 2019, Venice, Italy, 8/04/19. https://doi.org/10.1109/ISBI.2019.8759502

Magnetic resonance fingerprinting using recurrent neural networks. / Oksuz, Ilkay; Cruz, Gastao; Clough, James et al.
ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging. IEEE Computer Society, 2019. p. 1537-1540 8759502 (Proceedings - International Symposium on Biomedical Imaging; Hac. 2019-April).

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

TY - GEN

T1 - Magnetic resonance fingerprinting using recurrent neural networks

AU - Oksuz, Ilkay

AU - Cruz, Gastao

AU - Clough, James

AU - Bustin, Aurelien

AU - Fuin, Nicolo

AU - Botnar, Rene M.

AU - Prieto, Claudia

AU - King, Andrew P.

AU - Schnabel, Julia A.

PY - 2019/4

Y1 - 2019/4

N2 - Magnetic Resonance Fingerprinting (MRF) is a new approach to quantitative magnetic resonance imaging that allows simultaneous measurement of multiple tissue properties in a single, time-efficient acquisition. Standard MRF reconstructs parametric maps using dictionary matching and requires high computational time. We propose to perform MRF map reconstruction using a recurrent neural network, which exploits the time-dependent information of the MRF signal evolution. We evaluate our method on multiparametric synthetic signals and compare it to existing MRF map reconstruction approaches, including those based on neural networks. Our method achieves state-of-the-art estimates of T1 and T2 values. In addition, the reconstruction time is reduced compared to dictionary-matching based approach.

AB - Magnetic Resonance Fingerprinting (MRF) is a new approach to quantitative magnetic resonance imaging that allows simultaneous measurement of multiple tissue properties in a single, time-efficient acquisition. Standard MRF reconstructs parametric maps using dictionary matching and requires high computational time. We propose to perform MRF map reconstruction using a recurrent neural network, which exploits the time-dependent information of the MRF signal evolution. We evaluate our method on multiparametric synthetic signals and compare it to existing MRF map reconstruction approaches, including those based on neural networks. Our method achieves state-of-the-art estimates of T1 and T2 values. In addition, the reconstruction time is reduced compared to dictionary-matching based approach.

KW - Gru

KW - Lstm

KW - Magnetic resonance fingerprinting

KW - Parameter mapping

KW - Recurrent neural networks

UR - https://www.scopus.com/pages/publications/85073892391

U2 - 10.1109/ISBI.2019.8759502

DO - 10.1109/ISBI.2019.8759502

M3 - Conference contribution

AN - SCOPUS:85073892391

T3 - Proceedings - International Symposium on Biomedical Imaging

SP - 1537

EP - 1540

BT - ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging

PB - IEEE Computer Society

T2 - 16th IEEE International Symposium on Biomedical Imaging, ISBI 2019

Y2 - 8 April 2019 through 11 April 2019

ER -

Magnetic resonance fingerprinting using recurrent neural networks

Özet

Yayın serisi

???event.eventtypes.event.conference???

Bibliyografik not

Finansman

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

Alıntı Yap