PDQ is a set of MATLAB functions for detecting sphere-shaped deposits of magnetically susceptible material (i.e., magnetic dipoles) in MRI datasets, measuring their magnetic moment. Deposits of interest include SPIO-labeled cells and magnetocapsules.
Unpublished results suggest that PDQ is effective at distinguishing contrast due to dipoles from other intrinsic sources of hypointensity.
Publications that describe PDQ's function and exhibit results include:
1) Sensitive and automated detection of iron-oxide-labeled cells using phase image cross-correlation analysis. (http://tinyurl.com/qzora7a)
2) Automated detection and characterization of SPIO-labeled cells and capsules using magnetic field perturbations (http://tinyurl.com/bvomtde)
PDQ was developed in Ahrens Lab, Pittsburgh NMR Center for Biomedical Research, Carnegie Mellon University. Financial support was provided in part by the U.S. National Institutes of Health.
- Detects magnetic dipoles in MRI datasets
- Estimates magnetic dipole moment for detected dipoles
- Eliminates unreasonable dipole moments (e.g., too-weak dipoles found in noise, or too-strong dipoles found in air bubbles)
- Automatically masks out noise by fitting magnitude image to Rician & Gaussian distribution
- Works with non-isotropic datasets
- Processes multiple datasets, comparing dipoles quantitatively across them
- Calculates number of dipoles vs. distance from regions of interest (ROIs)
- Experimental: Estimates iron content within magnetic dipoles
- Experimental: Registers dipoles between different time points
- Experimental: Estimates dipole movements between different time points
- Experimental: Estimate 'best-fit' sphere radius for each dipole.
- Advanced: Detection templates: Detect dipoles located off-center of voxel boundaries; Simulate randomly-distributed spins to eliminate aliasing.
Be the first to post a review of MRI-PDQ:Phase Detection & Quantification!