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PURPOSE To establish a baseline of phase differences between tissues in a number of regions of the human brain as a means of detecting iron abnormalities using magnetic resonance imaging (MRI). MATERIALS AND METHODS A fully flow-compensated, three-dimensional (3D), high-resolution, gradient-echo (GRE) susceptibility-weighted imaging (SWI) sequence was(More)
PURPOSE To create a robust means to remove noise pixels using complex data. MATERIALS AND METHODS A receiver operating characteristic (ROC) curve was used to determine the appropriate choice of magnitude and phase thresholds as well as connectivity values to determine what pixels represent noise in the image. To fine-tune the results, a spike removal and(More)
The present piece of research studied the spontaneous alpha rhythm of the human brain by combining the use of a whole-cortex neuromagnetometer and Magnetic Resonance Imaging. Single trials of spontaneous brain activity were recorded from ten human subjects asked to rest, with their eyes either closed or open, in relaxed wakefulness. MEG measurements were(More)
In this work, we present a new method for predicting changes in tumor vascularity using only one flip angle in dynamic contrast-enhanced (DCE) imaging. The usual DCE approach finds the tissue initial T1 value T1(0) prior to injection of a contrast agent. We propose finding changes in the tissue contrast agent uptake characteristics pre- and postdrug(More)
This paper reports on performance assessment of an algorithm developed to align functional Magnetic Resonance Image (fMRI) time series. The algorithm is based on the assumption that the human brain is subject to rigid-body motion and has been devised by pipelining fiducial markers and tensor based registration methodologies. Feature extraction is performed(More)
This research presents signal-image post-processing techniques called Intensity-Curvature Measurement Approaches with application to the diagnosis of human brain tumors detected through Magnetic Resonance Imaging (MRI). Post-processing of the MRI of the human brain encompasses the following model functions: (i) bivariate cubic polynomial, (ii) bivariate(More)