Fast detection and reduction of local transient artifacts in resting-state fMRI

Hang Joon Jo, Richard C. Reynolds, Stephen J. Gotts, Daniel A. Handwerker, Irena Balzekas, Alex Martin, Robert W. Cox, Peter A. Bandettini

Research output: Contribution to journalArticle

Abstract

Image quality control (QC) is a critical and computationally intensive component of functional magnetic resonance imaging (fMRI). Artifacts caused by physiologic signals or hardware malfunctions are usually identified and removed during data processing offline, well after scanning sessions are complete. A system with the computational efficiency to identify and remove artifacts during image acquisition would permit rapid adjustment of protocols as issues arise during experiments. To improve the speed and accuracy of QC and functional image correction, we developed Fast Anatomy-Based Image Correction (Fast ANATICOR) with newly implemented nuisance models and an improved pipeline. We validated its performance on a dataset consisting of normal scans and scans containing known hardware-driven artifacts. Fast ANATICOR's increased processing speed may make real-time QC and image correction feasible as compared with the existing offline method.

Original languageEnglish
Article number103742
JournalComputers in Biology and Medicine
Volume120
DOIs
StatePublished - 2020 May

Keywords

  • Artifact detection
  • Functional MRI
  • Online denoising
  • Real-time fMRI
  • Resting-state connectivity
  • Sliding-windowed timeseries

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  • Cite this

    Jo, H. J., Reynolds, R. C., Gotts, S. J., Handwerker, D. A., Balzekas, I., Martin, A., Cox, R. W., & Bandettini, P. A. (2020). Fast detection and reduction of local transient artifacts in resting-state fMRI. Computers in Biology and Medicine, 120, [103742]. https://doi.org/10.1016/j.compbiomed.2020.103742