Measuring Risky Driving Behavior Using an mHealth Smartphone App: Development and Evaluation of gForce.

Background: Naturalistic driving studies, designed to objectively assess driving behavior and outcomes, are conducted by equipping vehicles with dedicated instrumentation (eg, accelerometers, gyroscopes, Global Positioning System, and cameras) that provide continuous recording of acceleration, location, videos, and still images for eventual retrieval and analyses. However, this research is limited by several factors: the cost of equipment installation; management and storage of the large amounts of data collected; and data reduction, coding, and analyses. Modern smartphone technology includes accelerometers built into phones, and the vast, global proliferation of smartphones could provide a possible low-cost alternative for assessing kinematic risky driving.

Application of an unsupervised multi-characteristic framework for intermediate-high risk prostate cancer localization using diffusion-weighted MRI.

Purpose: The aim of this proof-of-concept work is to propose an unsupervised framework that combines multiple parameters, in "positive-if-all-positive" manner, from different models to localize tumors.

Methods: A voxel-by-voxel analysis of the DW-MRI images of whole prostate was performed to obtain parametric maps for D*, D, f, and K using the IVIM and kurtosis models. Ten patients with moderate or high-risk prostate cancer were included in study.

A multivariate hypothesis testing framework for tissue clustering and classification of DTI data.

The primary aim of this work is to propose and investigate the effectiveness of a novel unsupervised tissue clustering and classification algorithm for diffusion tensor MRI (DTI) data. The proposed algorithm utilizes information about the degree of homogeneity of the distribution of diffusion tensors within voxels. We adapt frameworks proposed by Hext and Snedecor, where the null hypothesis of diffusion tensors belonging to the same distribution is assessed by an F-test.

Parsimonious model selection for tissue segmentation and classification applications: a study using simulated and experimental DTI data.

One aim of this work is to investigate the feasibility of using a hierarchy of models to describe diffusion tensor magnetic resonance (MR) data in fixed tissue. Parsimonious model selection criteria are used to choose among different models of diffusion within tissue. Using this information, we assess whether we can perform simultaneous tissue segmentation and classification.

New modeling and experimental framework to characterize hindered and restricted water diffusion in brain white matter.

To characterize anisotropic water diffusion in brain white matter, a theoretical framework is proposed that combines hindered and restricted models of water diffusion (CHARMED) and an experimental methodology that embodies features of diffusion tensor and q-space MRI. This model contains a hindered extra-axonal compartment, whose diffusion properties are characterized by an effective diffusion tensor, and an intra-axonal compartment, whose diffusion properties are characterized by a restricted model of diffusion within cylinders. The hindered model primarily explains the Gaussian signal attenuation observed at low b values; the restricted non-Gaussian model does so at high b.

AIR-SPAMM: alternative inversion recovery spatial modulation of magnetization for myocardial tagging.

Alternate inversion recovery spatial modulation of magnetization (AIR-SPAMM) can be used either for doubling the number of tags for a given tagging encoding gradient strength or for improving tagging contrast ratio. AIR-SPAMM requires only a single acquisition and utilizes inversion pulses spaced throughout the gradient recalled echo (GRE) cine acquisition to "lock" the recovering magnetization at a desired level. The theory of AIR-SPAMM is presented along with simulations and results from phantoms.

Quantitative assessment of left ventricular perfusion defects using real-time three-dimensional myocardial contrast echocardiography.

Quantitative assessment of perfusion defects with myocardial contrast echocardiography can be a valuable tool in the evaluation of patients with coronary artery disease. However, the use of 2-dimensional echocardiography for this purpose is limited to a restricted number of imaging planes. Real-time 3-dimensional echocardiography (RT3D) is a novel technique that provides instantaneous volumetric images.