Where is physiological noise lurking in k-space?

Research output: Contribution to conferencePosterProfessional

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Where is physiological noise lurking in k-space? / Karvonen, Toni; Solin, Arno; Garcia Fernandez, Angel; Tronarp, Filip; Särkkä, Simo; Lin, Fa-Hsuan.

2017. Poster session presented at International Society for Magnetic Resonance in Medicine Annual Meeting, Honolulu, United States.

Research output: Contribution to conferencePosterProfessional

Harvard

Karvonen, T, Solin, A, Garcia Fernandez, A, Tronarp, F, Särkkä, S & Lin, F-H 2017, 'Where is physiological noise lurking in k-space?' International Society for Magnetic Resonance in Medicine Annual Meeting, Honolulu, United States, 22/04/2017 - 27/04/2017, .

APA

Karvonen, T., Solin, A., Garcia Fernandez, A., Tronarp, F., Särkkä, S., & Lin, F-H. (2017). Where is physiological noise lurking in k-space?. Poster session presented at International Society for Magnetic Resonance in Medicine Annual Meeting, Honolulu, United States.

Vancouver

Karvonen T, Solin A, Garcia Fernandez A, Tronarp F, Särkkä S, Lin F-H. Where is physiological noise lurking in k-space?. 2017. Poster session presented at International Society for Magnetic Resonance in Medicine Annual Meeting, Honolulu, United States.

Author

Karvonen, Toni ; Solin, Arno ; Garcia Fernandez, Angel ; Tronarp, Filip ; Särkkä, Simo ; Lin, Fa-Hsuan. / Where is physiological noise lurking in k-space?. Poster session presented at International Society for Magnetic Resonance in Medicine Annual Meeting, Honolulu, United States.5 p.

Bibtex - Download

@conference{8c4a0ea1b5974c75b67203d1751bb1c8,
title = "Where is physiological noise lurking in k-space?",
abstract = "We analyze the structure of physiological noise in the k-space of BOLD fMRI. We use DRIFTER which is an algorithm based on optimal Bayesian smoothing techniques for separation of the fMRI signal to a BOLD signal component and physiological noises. DRIFTER is run independently for each spatial frequency and it is shown that the physiological noise lies in the k-space points with low spatial frequency and that its amplitude is proportional to the BOLD signal. This result suggests that we can lower the computational burden without losing estimation accuracy by running DRIFTER only on a subset of k-space points.",
author = "Toni Karvonen and Arno Solin and {Garcia Fernandez}, Angel and Filip Tronarp and Simo S{\"a}rkk{\"a} and Fa-Hsuan Lin",
note = "https://users.aalto.fi/~karvont2/pdf/ISMRM2017.pdf Proceedings of the International Society for Magnetic Resonance in Medicine, ISSN 1545-4428, 5300. Suomen Akatemia: 266940 ja 298131; International Society for Magnetic Resonance in Medicine Annual Meeting, ISMRM ; Conference date: 22-04-2017 Through 27-04-2017",
year = "2017",
language = "English",

}

RIS - Download

TY - CONF

T1 - Where is physiological noise lurking in k-space?

AU - Karvonen, Toni

AU - Solin, Arno

AU - Garcia Fernandez, Angel

AU - Tronarp, Filip

AU - Särkkä, Simo

AU - Lin, Fa-Hsuan

N1 - https://users.aalto.fi/~karvont2/pdf/ISMRM2017.pdf Proceedings of the International Society for Magnetic Resonance in Medicine, ISSN 1545-4428, 5300. Suomen Akatemia: 266940 ja 298131

PY - 2017

Y1 - 2017

N2 - We analyze the structure of physiological noise in the k-space of BOLD fMRI. We use DRIFTER which is an algorithm based on optimal Bayesian smoothing techniques for separation of the fMRI signal to a BOLD signal component and physiological noises. DRIFTER is run independently for each spatial frequency and it is shown that the physiological noise lies in the k-space points with low spatial frequency and that its amplitude is proportional to the BOLD signal. This result suggests that we can lower the computational burden without losing estimation accuracy by running DRIFTER only on a subset of k-space points.

AB - We analyze the structure of physiological noise in the k-space of BOLD fMRI. We use DRIFTER which is an algorithm based on optimal Bayesian smoothing techniques for separation of the fMRI signal to a BOLD signal component and physiological noises. DRIFTER is run independently for each spatial frequency and it is shown that the physiological noise lies in the k-space points with low spatial frequency and that its amplitude is proportional to the BOLD signal. This result suggests that we can lower the computational burden without losing estimation accuracy by running DRIFTER only on a subset of k-space points.

M3 - Poster

ER -

ID: 32113183