Blind estimation for localized low contrast-to-noise ratio BOLD signals

Ian C. Atkinson, Farzad Kamalabadi, Douglas L. Jones, Keith R. Thulborn

Research output: Contribution to journalArticlepeer-review


Accurate detection of low contrast-to-noise ratio (CNR) blood oxygenation level dependent (BOLD) signals in functional magnetic resonance imaging (fMRI) data is important for presurgical planning and cognitive research. Robust detection is challenging in small regions of low CNR activation since the probability of detecting each individual voxel is low. We present a processing technique for improving the detection of localized low CNR BOLD signals in fMRI data. When applied to synthetic fMRI data, this blind estimation scheme significantly improves the probability of correctly detecting voxels in a small region of activation with a CNR between 0.5 and 1.0 compared to the standard general linear model approach. More activation is detected in expected (based on input stimulus) regions of experimental data after processing with the proposed technique.

Original languageEnglish (US)
Pages (from-to)879-890
Number of pages12
JournalIEEE Journal on Selected Topics in Signal Processing
Issue number6
StatePublished - 2008


  • BOLD contrast
  • Brain mapping
  • Estimation
  • Functional magnetic resonance imaging
  • Magnetic resonance imaging
  • Signal detection
  • Signal estimation

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering


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