OPINION STATEMENT Cerebral small vessel disease (SVD) is characterised by damage to deep grey and white matter structures of the brain and is responsible for a diverse range of clinical problems that include stroke and dementia. In this review, we describe advances in neuroimaging published since January 2015, mainly with magnetic resonance imaging (MRI), that, in general, are improving quantif...

Singular Value Decomposition (SVD) is a popular approach in various network applications, such as link prediction and network parameter characterization. Incremental SVD approaches are proposed to process newly changed nodes and edges in dynamic networks. However, incremental SVD approaches suffer from serious error accumulation inevitably due to approximation on incremental updates. SVD restar...

The main contribution of this paper is to demonstrate that a new randomized SVD algorithm, proposed by Drineas et. al. in [4], is not only of theoretical interest but also a viable and fast alternative to traditional SVD algorithms in applications (e.g. image processing). This algorithm samples a constant number of rows (or columns) of the matrix, scales them appropriately to form a small matri...

In this paper, we propose a novel technique for video shot segmentation and classiication based on the Singular Value Decomposition (SVD). For the input video sequence, we create a feature-frame matrix A, and perform the SVD on it. From this SVD, we are able to not only derive the reened feature space to better segment the video sequence along time axis, but also deene metrics to enable classii...

An adaptive Singular Value Decomposition (SVD) algorithm is an optimal method to obtain spatial multiplexing gain MIMO-OFDM systems. We present an orthogonal reconstruction scheme to obtain more accurate SVD outputs and then the system performance will be greatly enhanced. Moreover this project reduces high cost of implementation and high decomposing latency. Finally adaptive SVD engine is simu...

Objective We explored the association between the total small vessel disease (SVD) score obtained with magnetic resonance imaging and risk factors and outcomes in the Japanese population. Methods The presence of SVD features, including lacunes, cerebral microbleeds, white matter changes, and basal ganglia perivascular spaces on MRI, was summed to obtain a "total SVD score" (range 0-4). Ordinal ...