症例の予後改善のための,電子ビームCT,4列～320列CTを用いた循環器領域の新しい臨床診断学の開発への貢献

I went to the Stanford University Department of Radiology\u27s three-dimensional (3D) imaging laboratory from 1996 to 1999 to study a novel 3D image processing technique using electron beam computed tomography (CT). When I returned to Japan, I found that multi-slice CT had been available in daily practice since 1998. We have published a total of 152 peer-reviewed papers on diagnostic images in the field of cardiovascular disease. In 2003, when 16-slice CT was available for use in general hospitals, we successfully developed a prototype 256-slice cone-beam CT at the National Institute of Radiological Sciences. We produced several papers discussing the utilities of this prototype CT in both animal and phantom experiments, the concepts and ideas that were currently used for cardiac perfusion and myocardium characteristic study. In 2010, our paper was used as a reference in the American College of Cardiology Foundation Expert Consensus Guideline. The our current topics presented include coronary artery stenosis, coronary arterial plaques, the characteristics of the myocardium, the anatomy of structural and congenital heart disease, and the cardiac function, all using 16-320 slice CT with reduced radiation exposure in CT acquisition. Furthermore, we are now performing novel clinical CT studies combined magnetic resonance imaging (MRI), positron emission tomography, and echocardiography. Using previous image data, we analyzed an epidemiology study using CT findings to predict the occurrence of major cardiovascular adverse events over long-term follow-up periods of more than 100 months (median), one of the longest follow-up periods documented in the literature. We also need to obtain accurate diagnoses for subjects with cardiac failure or fatal arrhythmia of unknown origin, allowing them to receive specific effective therapy for their possible cardiac amyloidosis, cardiac sarcoidosis, or Fabry\u27s disease. Of course, in all CT imaging techniques used for evaluation and monitoring of cardiovascular risk

Evaluation of an epoxy resin containing a carboxylic acid-terminated fluoroligomer for use as matrix for glass fibre composites

Fibre reinforced plastics composites have been used in many engineering application as structural materials due to their high specific stiffness and strength. However the brittleness of composite materials prevents them from being used in high demanding applications. Toughness enhancement of fibre reinforced plastics composites, therefore, has aroused considerable interest in the composites industry. In recent years many studies have been conducted by using two-phase rubber modified thermosetting matrix resins to improve the energy absorbing capabilities of composite materials. [Continues.

Low-dimensional approximation searching strategy for transfer entropy from non-uniform embedding

<div><p>Transfer entropy from non-uniform embedding is a popular tool for the inference of causal relationships among dynamical subsystems. In this study we present an approach that makes use of low-dimensional conditional mutual information quantities to decompose the original high-dimensional conditional mutual information in the searching procedure of non-uniform embedding for significant variables at different lags. We perform a series of simulation experiments to assess the sensitivity and specificity of our proposed method to demonstrate its advantage compared to previous algorithms. The results provide concrete evidence that low-dimensional approximations can help to improve the statistical accuracy of transfer entropy in multivariate causality analysis and yield a better performance over other methods. The proposed method is especially efficient as the data length grows.</p></div

Sensitivity, specificity and F1 score values obtained from Model C by binning(-b) and NN(-n) estimators.

<p>Sensitivity, specificity and F1 score values obtained from Model C by binning(-b) and NN(-n) estimators.</p

ROC curves for Model E with varying noise and coupling strengths.

<p>Sensitivity and specificity are obtained for models with a varying noise from 0.01 to 0.04 (marked in the figure). The first row shows results from the methods applying binning estimator and second row for NN estimator. Column 1 to 3 is with different coupling strength from 0.1, 0.3 to 0.5. Each simulation was performed 100 runs with data length 512.</p

Sensitivity, specificity and F1 score values obtained from Model E by binning(-b) and NN(-n) estimators.

<p>Sensitivity, specificity and F1 score values obtained from Model E by binning(-b) and NN(-n) estimators.</p

Results for an epileptic EEG recording.

<p>Matrices of causalities reflect before (top) and during (down) the clinical onset of a seizure from an epileptic patient, the results are respectively averaged from 8 recordings. Contacts 1 to 64 belong to a cortical electrode grid, and contacts 65 to 76 to two depth electrode strips. The values are computed by traditional non-uniform transfer entropy (TE) and low-dimensional approximation approach (LA). The directions of causal influence are from row to column. The brighter colors correspond to more significant values.</p

ROC curves for Model B.

<p>Sensitivity and specificity are obtained by gradually increasing the time series length from 256 to 1024 points.</p

Matrix representations of the corresponding causalities for Model D.

<p>Retrieved by traditional TE method and two low-dimensional approximation methods, respectively by using binning entropy estimator (a, b, c) and NN entropy estimator (d, e, f) over 100 simulations of 1024 time points. The results are shown with color revealing the magnitude and transparency indicating the significance. The directions of causal influence are from row to column.</p

Sensitivity, specificity and F1 score values obtained from Model G by binning(-b) and NN(-n) estimators with different data lengths and coupling strengths.

<p>Sensitivity, specificity and F1 score values obtained from Model G by binning(-b) and NN(-n) estimators with different data lengths and coupling strengths.</p