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Spatial resolution enhancement using sensitivity-encoded echo-planar imaging at 3T in a typical motor paradigm


Schmidt, Conny F; Pruessmann, Klaas P; Boesiger, Peter (2007). Spatial resolution enhancement using sensitivity-encoded echo-planar imaging at 3T in a typical motor paradigm. Computerized Medical Imaging and Graphics, 31(8):704-714.

Abstract

We employ a single-shot sensitivity-encoded (SENSE) gradient-echo EPI acquisition in order to enhance spatial resolution in a typical motor fMRI experiment at 3T. Functional time series were acquired with an acquisition matrix size of 56x192 within a readout time of 82 ms, yielding an effective in-plane resolution of 0.94 mmx0.94 mm and compared to a conventional acquisition. Our data suggest that fMRI can readily be performed with a spatial resolution adapted to detailed cortical functional topography. However, in all potential applications the specific behavior of spatial specificity and statistical sensitivity needs to be taken into account.

Abstract

We employ a single-shot sensitivity-encoded (SENSE) gradient-echo EPI acquisition in order to enhance spatial resolution in a typical motor fMRI experiment at 3T. Functional time series were acquired with an acquisition matrix size of 56x192 within a readout time of 82 ms, yielding an effective in-plane resolution of 0.94 mmx0.94 mm and compared to a conventional acquisition. Our data suggest that fMRI can readily be performed with a spatial resolution adapted to detailed cortical functional topography. However, in all potential applications the specific behavior of spatial specificity and statistical sensitivity needs to be taken into account.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Institute of Biomedical Engineering
Dewey Decimal Classification:170 Ethics
610 Medicine & health
Scopus Subject Areas:Health Sciences > Radiological and Ultrasound Technology
Health Sciences > Radiology, Nuclear Medicine and Imaging
Physical Sciences > Computer Vision and Pattern Recognition
Health Sciences > Health Informatics
Physical Sciences > Computer Graphics and Computer-Aided Design
Language:English
Date:2007
Deposited On:21 May 2014 07:22
Last Modified:24 Jan 2022 04:09
Publisher:Pergamon
ISSN:0895-6111
OA Status:Closed
Publisher DOI:https://doi.org/10.1016/j.compmedimag.2007.08.011
PubMed ID:17936582
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