Image Augmentation using Radial Transform for Training Deep Neural Networks

Deep learning models have a large number of free parameters that must be estimated by efficient training of the models on a large number of training data samples to increase their generalization performance. In real-world applications, the data available to train these networks is often limited or imbalanced. We propose a sampling method based on the radial transform in a polar coordinate system for image augmentation to facilitate the training of deep learning models from limited source data. This pixel-wise transform provides representations of the original image in the polar coordinate system by generating a new image from each pixel. This technique can generate radial transformed images up to the number of pixels in the original image to increase the diversity of poorly represented image classes. Our experiments show improved generalization performance in training deep convolutional neural networks with radial transformed images.Comment: This paper is accepted for presentation at IEEE International Conference on Acoustics, Speech and Signal Processing (IEEE ICASSP), 201

Music Intervention Approaches for Alzheimer’s Disease: A Review of the Literature

Music interventions have been widely adopted as a potential non-pharmacological therapy for patients with Alzheimer’s disease (AD) to treat cognitive and/or behavioral symptoms of the disease. In spite of the prevalence of such therapies, evidence for their effectiveness report mixed results in the literature. The purpose of this narrative review is to investigate the effectiveness of various intervention strategies (music therapy vs. music listening techniques) and music type used in the intervention (individualized vs. non-individualized music) on cognitive and behavioral outcomes for persons with AD. Databases were searched for studies using either active music therapy or music listening techniques over the last 10 years. These studies were in English, included persons with AD dementia, and whose protocol gathered pre- and post-intervention outcome measures. We initially identified 206 papers which were then reduced to 167 after removing duplicates. Further review yielded 13 papers which were extensively reviewed, resulting in a final sample of six papers. Our analysis of these papers suggested that, regardless of the music intervention approach, individualized music regimens provided the best outcomes for the patient. Furthermore, music listening may act as a relaxation technique and therefore provide a long-term impact for the patient, while active music therapy may acts to engage participants through social interaction and provide acute benefits. Our findings suggest that music techniques can be utilized in various ways to improve behavior and cognition

Blood Velocity and Volumetric Flow Rate Calculated from Dynamic 4D CT Angiography using a Time of Flight Approach

Purpose: A time of flight approach to the analysis of 4D CT angiography is examined to calculate blood flow in arteries. Materials and Methods: Software was written to track contrast bolus TOF along a central vessel axis. Time density curves were analyzed to determine bolus time to peak at successive vessel cross-sections which were plotted against vessel path length. A line of best fit was plotted through the resulting data and 1/slope provided a measurement of velocity. Results: Validation was successful in simulation and in flow phantoms, though quality of results depended strongly on quality of curve fit. In phantoms and in vivo, accuracy and reproducibility of measurements improved with longer path lengths and, in vivo, depended on the avoidance of venous contamination. Conclusions: Quantitative functional intravascular information such as blood velocity and flow rate may be calculated from 4D CT angiography.MAS