Automated perfusion-weighted MRI metrics via localized arterial input functions

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.

Bibliographic Details
Main Author: Lorenz, Cory, 1981-
Other Authors: A. Gregory Sorensen.
Format: Thesis
Language:en_US
Published: Massachusetts Institute of Technology 2005
Subjects:
Online Access:http://hdl.handle.net/1721.1/28435
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author Lorenz, Cory, 1981-
author2 A. Gregory Sorensen.
author_facet A. Gregory Sorensen.
Lorenz, Cory, 1981-
author_sort Lorenz, Cory, 1981-
collection MIT
description Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.
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institution Massachusetts Institute of Technology
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spelling mit-1721.1/284352019-04-11T00:12:03Z Automated perfusion-weighted MRI metrics via localized arterial input functions Automated perfusion-weighted magnetic resonance imaging metrics via localized AIF Lorenz, Cory, 1981- A. Gregory Sorensen. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004. Includes bibliographical references (p. 57-58). This thesis describes and validates a new method for calculating perfusion-weighted MRI (PWI) metrics, a non-invasive technique for calculating cerebral blood flow by tracking a bolus of contrast agent. Past methods to do this calculation require human intermediaries and can lead to errors in the presence of delay and dispersion of the contrast bolus, situations which occur commonly in the pathological conditions which require PWI. The new method described calculates perfusion metrics by defining an arterial input function (AIF) for every voxel in the brain based upon the voxels in close proximity to it. This allows for automated calculation of perfusion metrics, and the localized nature of the AIFs creates an implicit regard for delay and dispersion. This thesis demonstrates that this local AIF method is indeed able to correct flow misestimations due to delay and dispersion, and that it is also more useful for predicting tissue outcome post-stroke. by Cory Lorenz. M.Eng. 2005-09-26T20:25:49Z 2005-09-26T20:25:49Z 2004 2004 Thesis http://hdl.handle.net/1721.1/28435 57002923 en_US M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 70 p. 3475859 bytes 3482783 bytes application/pdf application/pdf application/pdf Massachusetts Institute of Technology
spellingShingle Electrical Engineering and Computer Science.
Lorenz, Cory, 1981-
Automated perfusion-weighted MRI metrics via localized arterial input functions
title Automated perfusion-weighted MRI metrics via localized arterial input functions
title_full Automated perfusion-weighted MRI metrics via localized arterial input functions
title_fullStr Automated perfusion-weighted MRI metrics via localized arterial input functions
title_full_unstemmed Automated perfusion-weighted MRI metrics via localized arterial input functions
title_short Automated perfusion-weighted MRI metrics via localized arterial input functions
title_sort automated perfusion weighted mri metrics via localized arterial input functions
topic Electrical Engineering and Computer Science.
url http://hdl.handle.net/1721.1/28435
work_keys_str_mv AT lorenzcory1981 automatedperfusionweightedmrimetricsvialocalizedarterialinputfunctions
AT lorenzcory1981 automatedperfusionweightedmagneticresonanceimagingmetricsvialocalizedaif