Charles Saylor | PubMed Health

PubMed2006

SmartPhantom--an fMRI simulator.

Many informatics tools have emerged to process the voluminous and complex data generated by functional magnetic resonance imaging (fMRI). The interpretation of fMRI exams is largely determined by these tools. However, their performance is hard to evaluate because there is no independent means of calibration. A novel fMRI calibration system called SmartPhantom has been developed to simulate functional blood oxygen level dependent (BOLD) imaging. SmartPhantom contains a quadrature radio frequency coil, comprising two perpendicular planar loops that can be externally activated or deactivated. The system is able to produce reasonably uniform signal enhancements in a calibration sample surrounded by the two loops during an MRI scan. The enhancement is controlled well in both magnitude and predefined timing and produces BOLD-like signals. Characteristics of SmartPhantom are discussed in detail, followed by a comparison of fMRI informatics tools. Two fMRI data sets are acquired with the SmartPhantom. One with high signal-to-noise ratio provides the calibration. Another with lower SNR is input into three software packages (BrainVoyager, FSL and Statistical Parametric Mapping 2) for data preprocessing and statistical analysis. Results from the three packages are compared in both sensitivity of detecting the activation and correlation between the predicted activation and calibration.

Calibration↗

PubMed2005

Application of partial differential equation-based inpainting on sensitivity maps.

Inpainting is an image interpolation method. Partial differential equation (PDE)-based digital inpainting techniques are finding broad applications. In this paper, PDE-based inpainting techniques are applied to the field of MR parallel imaging. A novel model and its corresponding numerical method are introduced. This model is then applied to sensitivity maps. Coil sensitivity maps are important for parallel imaging, and they often require extrapolation and hole filling (holes being dark regions of low signal in MR images). These problems can be solved simultaneously by the application of inpainting techniques. Experiments for determining coil sensitivity maps for phantoms and cardiac MR images demonstrate the accuracy of the proposed model. Images generated using sensitivity encoding (SENSE) that utilizes inpainted sensitivity maps, thin-plate spline (TPS) estimated sensitivity maps, and Gaussian kernel smoothed (GKS) sensitivity maps are compared. From the experimental results, it can be seen that inpainted sensitivity maps produce better results than GKS sensitivity maps. The TPS method generates results similar to those of the inpainting technique but is much more time-consuming.

Algorithms↗