http://www.nitrc.org/forum/forum.php?forum_id=5706 <table border="0" width="100%"><tr><td align="left"/></tr></table> <p><b>High spatial resolution compressed sensing (HSPARSE) functional MRI.</b></p> <p>Magn Reson Med. 2015 Oct 29;</p> <p>Authors: Fang Z, Van Le N, Choy M, Lee JH</p> <p>Abstract<br/> PURPOSE: To propose a novel compressed sensing (CS) high spatial resolution functional MRI (fMRI) method and demonstrate the advantages and limitations of using CS for high spatial resolution fMRI.<br/> METHODS: A randomly undersampled variable density spiral trajectory enabling an acceleration factor of 5.3 was designed with a balanced steady state free precession sequence to achieve high spatial resolution data acquisition. A modified k-t SPARSE method was then implemented and applied with a strategy to optimize regularization parameters for consistent, high quality CS reconstruction.<br/> RESULTS: The proposed method improves spatial resolution by six-fold with 12 to 47% contrast-to-noise ratio (CNR), 33 to 117% F-value improvement and maintains the same temporal resolution. It also achieves high sensitivity of 69 to 99% compared the original ground-truth, small false positive rate of less than 0.05 and low hemodynamic response function distortion across a wide range of CNRs. The proposed method is robust to physiological noise and enables detection of layer-specific activities in vivo, which cannot be resolved using the highest spatial resolution Nyquist acquisition.<br/> CONCLUSION: The proposed method enables high spatial resolution fMRI that can resolve layer-specific brain activity and demonstrates the significant improvement that CS can bring to high spatial resolution fMRI. Magn Reson Med, 2015. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.<br/> </p><p>PMID: 26511101 [PubMed - as supplied by publisher]</p> en-us Copyright 2000-2026 NITRC OSI Sun, 03 May 2026 19:55:51 GMT http://blogs.law.harvard.edu/tech/rss NITRC RSS generator