Ultra-fast fMRI imaging with high-fidelity activation map

Neelam Sinha, Manojkumar Saranathan, A. G. Ramakrishnan, Juan Zhou, Jagath C. Rajapakse

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Functional Magnetic Resonance Imaging (fMRI) requires ultra-fast imaging in order to capture the on-going spatio-temporal dynamics of the cognitive task. We make use of correlations in both k-space and time, and thereby reconstruct the time series by acquiring only a fraction of the data, using an improved form of the well-known dynamic imaging technique k-t BLAST (Broad-use Linear Acquisition Speed-up Technique), k-t BLAST (k-tB) works by unwrapping the aliased Fourier conjugate space of k-t ( y-f space). The unwrapping process makes use of an estimate of the true y-f space, obtained by acquiring a blurred unaliased version. In this paper, we propose two changes to the existing algorithm. Firstly, we improve the map estimate using generalized series reconstruction. The second change is to incorporate phase constraints from the training map. The proposed technique is compared with existing k-tB on visual stimulation fMRI data obtained on 5 volunteers. Results show that the proposed changes lead to gain in temporal resolution by as much as a factor of 6. Performance evaluation is carried out by comparing activation maps obtained using reconstructed images, against that obtained from the true images. We observe upto 10dB improvement in PSNR of activation maps, Besides, RMSE reduction on fMRI images, of about 10% averaged over the entire time series, with a peak improvement of 35% compared to the existing k-tB, averaged over 5 data sets, is also observed.

Original languageEnglish (US)
Title of host publicationNeural Information Processing - 13th International Conference, ICONIP 2006, Proceedings
PublisherSpringer-Verlag
Pages361-368
Number of pages8
ISBN (Print)3540464816, 9783540464815
DOIs
StatePublished - 2006
Externally publishedYes
Event13th International Conference on Neural Information Processing, ICONIP 2006 - Hong Kong, China
Duration: Oct 3 2006Oct 6 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4233 LNCS - II
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference13th International Conference on Neural Information Processing, ICONIP 2006
Country/TerritoryChina
CityHong Kong
Period10/3/0610/6/06

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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