Giovanna Rizzo

TL;DR: It is suggested that, in some brain regions, non-negative constraints alone may not be sufficient to reduce spurious fibre orientations, and a newly developed spherical deconvolution algorithm based on an adaptive regularization (damped version of the Richardson-Lucy algorithm) has the potential for better characterizing white matter anatomy and the integrity of pathological tissue.

TL;DR: Methods of HRV signal processing by using autoregressive (AR) modeling and power spectral density estimate are illustrated, which provides a simple non-invasive analysis, based on the processing of spontaneous oscillations in heart rate.

TL;DR: This study shows that the quantification of helical blood flow in vivo is feasible, and it might allow detection of anomalies in the expected physiological development of helicals flow in aorta and accordingly, could be used in a diagnostic/prognostic index for clinical practice.

TL;DR: Simulations show the ability of this method to correctly separate fiber crossing, even in the presence of noisy data, with lower signal-to-noise ratio, and imprecision in the impulse response function imposed during deconvolution.

TL;DR: The hemodynamics within the aorta of five healthy humans were investigated and group analysis suggested that aortic helical blood flow dynamics is an emerging behavior that is common to normal individuals, and the results suggest that helical flow might be caused by natural optimization of fluid transport processes in the cardiovascular system.