The purpose of this study was to introduce an improved tool for automated classification of event-related potentials (ERPs) using spatiotemporally parcellated events incorporated into a functional brain network activation (BNA) analysis. The auditory oddball ERP paradigm was selected to demonstrate and evaluate the improved tool. Methods: The ERPs of each subject were decomposed into major dyna...

The spatial pattern of forest fire locations is of interest for fire occurrence prediction and for understanding the role of fire in landscape processes. A spatial statistical analysis of lightning-caused fires in the province of Ontario, between 1976 and 1998, was carried out to investigate the spatial pattern of fires, the way they depart from randomness, and the scales at which spatial corre...

Combining flux tower measurements with remote sensing or land surface models is generally regarded as an efficient method to scale up flux data from site to region. However, due to the heterogeneous nature of the vegetated land surface, the changing flux source areas and the mismatching between ground source areas and remote sensing grids, direct use of in-situ flux measurements can lead to maj...

Self-organizing map(SOM) have been widely applied in clustering, this paper focused on centroids of clusters and what they reveal. When the input vectors consists of time, latitude and longitude, the map can be strongly linked to physical world, providing valuable information. Beyond basic clustering, a novel approach to address the temporal element is developed, enabling 3D SOM to track behavi...

This paper addresses the use of spatiotemporal transform methods applied to the analysis of dynamic image sequences and the characterization of image motion. Image motion including a divergent component (resulting from a looming camera component) is analyzed in the spatiotemporal Mellin Transform (MT) domain, resulting in the separation of the spectrum into two parts: a structural term correspo...

in this paper, we review novel techniques in the emerging field of spatiotemporal 4d pet imaging. we will discuss existing limitations in conventional dynamic pet imaging which involves independent reconstruction of dynamic pet datasets. various approaches that seek to attempt some or all of these limitations are reviewed in this work, including techniques that utilize iterative temporal smooth...

Space and time are two critical components of many real world systems. For this reason, analysis of anomalies in spatiotemporal data has been a great of interest. In this work, application of tensor decomposition and eigenspace techniques on spatiotemporal hotspot detection is investigated. An algorithm called SST-Hotspot is proposed which accounts for spatiotemporal variations in data and dete...

PURPOSE Analyzing spatiotemporal enhancement patterns is an important task for the differential diagnosis of breast tumors in dynamic contrast-enhanced MRI (DCE-MRI), and yet remains challenging because of complexities in analyzing the time-series of three-dimensional image data. The authors propose a novel approach to breast MRI computer-aided diagnosis (CAD) using a multilevel analysis of spa...

A technique for building a three-dimensional description of a static scene from a spatiotemporal image is presented. This technique utilizes Homocentric Spherical Spatiotemporal Image (HSSI) analysis and makes allowances for camera rotation, which is a wider class of camera motion than that in ordinary spatiotemporal image analysis. Experiments with real images from a translating and rotating c...

The objective of this study was to investigate spatiotemporal characteristics with gait variability in patients with freezing of gait (FOG) after hypoxic-ischemic brain injury (HIBI).Eleven patients showing FOG after HIBI and 15 normal controls were consecutively enrolled. We performed gait analysis using a computerized gait system (VICON MX-T10 Motion Analysis System) and compared spatiotempor...