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Simultaneous registration and activa...

Orchard, Jeffrey John.

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Simultaneous registration and activation detection: Overcoming activation-induced registration errors in functional MRI.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Simultaneous registration and activation detection: Overcoming activation-induced registration errors in functional MRI./
作者:	Orchard, Jeffrey John.
面頁冊數:	136 p.
附註:	Source: Dissertation Abstracts International, Volume: 64-08, Section: B, page: 3910.
Contained By:	Dissertation Abstracts International64-08B.
標題:	Computer Science. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=NQ81604
ISBN:	0612816044

Simultaneous registration and activation detection: Overcoming activation-induced registration errors in functional MRI.
Orchard, Jeffrey John.

Simultaneous registration and activation detection: Overcoming activation-induced registration errors in functional MRI. - 136 p.

Source: Dissertation Abstracts International, Volume: 64-08, Section: B, page: 3910.

Thesis (Ph.D.)--Simon Fraser University (Canada), 2003.

In the processing of functional magnetic resonance imaging (fMRI) data, motion correction is typically performed before activation detection. However, on high-field MR scanners (3 T and higher), the strength of the blood oxygen level dependent (BOLD) signal can cause registration algorithms to produce motion estimates that have stimulus-correlated errors. Motion compensation using these biased motion estimates can result in both false-positive and false-negative regions of activation.

ISBN: 0612816044Subjects--Topical Terms:

626642
Computer Science.

Simultaneous registration and activation detection: Overcoming activation-induced registration errors in functional MRI.
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520 $a In the processing of functional magnetic resonance imaging (fMRI) data, motion correction is typically performed before activation detection. However, on high-field MR scanners (3 T and higher), the strength of the blood oxygen level dependent (BOLD) signal can cause registration algorithms to produce motion estimates that have stimulus-correlated errors. Motion compensation using these biased motion estimates can result in both false-positive and false-negative regions of activation.
520 $a By formulating the registration and activation detection problems into a single least-squares problem, both the motion estimates and activation map can be solved for simultaneously. However, the solution is not unique and an additional constraint is used to find a solution that is appropriate. This constrained optimization problem can be solved efficiently, and two equivalent methods are proposed and demonstrated on both simulated and in vivo datasets.
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