Campus Units

Statistics

Document Type

Article

Publication Version

Accepted Manuscript

Publication Date

5-7-2019

Journal or Book Title

IEEE Transactions on Medical Imaging

Volume

38

Issue

12

First Page

2821

Last Page

2828

DOI

10.1109/TMI.2019.2915052

Abstract

Functional magnetic resonance imaging is a noninvasive tool for studying cerebral function. Many factors challenge activation detection, especially in low-signal scenarios that arise in the performance of high-level cognitive tasks. We provide a fully automated fast adaptive smoothing and thresholding (FAST) algorithm that uses smoothing and extreme value theory on correlated statistical parametric maps for thresholding. Performance on experiments spanning a range of low-signal settings is very encouraging. The methodology also performs well in a study to identify the cerebral regions that perceive only-auditory-reliable or only-visual-reliable speech stimuli.

Comments

This is a manuscript of an article published as Almodóvar-Rivera, Israel, and Ranjan Maitra. "FAST adaptive smoothing and thresholding for improved activation detection in low-signal fMRI." IEEE Transactions on Medical Imaging 38, no. 12 (2019): 2821-2828. DOI: 10.1109/TMI.2019.2915052. Posted with permission.

Rights

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Copyright Owner

IEEE

Language

en

File Format

application/pdf

Published Version

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