State Estimation with Structural Priors in fMRI

We propose a state estimation approach for functional magnetic resonance imaging (fMRI). In state estimation, time-dependent image reconstruction problem is modeled by separate state evolution and observation models, and the objective is to estimate the time series of system states, given the models and the time-dependent measurement data. Our method computes the state estimates by using the Kalman filter (KF) and Kalman smoother (KS) algorithms. We propose to complement the state estimation formulation with a structural prior which can be derived from the anatomical MRI, acquired as a part of the fMRI protocol. Two different constructions of the structural prior are considered. The first one is a structured smoothness prior where the state observation matrix is augmented with a spatially weighted regularization matrix which promotes structural similarity of the gradient of the unknown image with the gradient of the anatomical image. The second approach is based on applying structured total variation denoising to the KF estimate at each time step of the Kalman recursions. The proposed approaches are evaluated using simulated and experimental, radially sampled, small animal fMRI data from a rat brain. In our method, the state estimates are updated after each new spoke of radial data becomes available, leading to faster frame rate compared to the conventional image reconstruction approaches. The results are compared to a sliding window method and a conventional reconstruction which produces new image only after a full circle of k-space spokes becomes available. The results suggest that the state estimation approach with the structural prior can improve both spatial and temporal resolution of fMRI.     

Aboveground forest biomass derived using multiple dates of WorldView-2 stereo-imagery: quantifying the improvement in estimation accuracy

ABSTRACT

The aim of this study was to investigate the capabilities of two date satellite-derived image-based point clouds (IPCs) to estimate forest aboveground biomass (AGB). The data sets used include panchromatic WorldView-2 stereo-imagery with 0.46 m spatial resolution representing 2014 and 2016 and a detailed digital elevation model derived from airborne laser scanning data. Altogether, 332 field sample plots with an area of 256 m² were used for model development and validation. Predictors describing forest height, density, and variation in height were extracted from the IPC 2014 and 2016 and used in k-nearest neighbour imputation models developed with sample plot data for predicting AGB. AGB predictions for 2014 (AGB₂₀₁₄) were projected to 2016 using growth models (AGB_{Projected_2016}) and combined with the AGB estimates derived from the 2016 data (AGB₂₀₁₆). AGB prediction model developed with 2014 data was also applied to 2016 data (AGB_{2016_pred2014}). Based on our results, the change in the 90^th percentile of height derived from the WorldView-2 IPC was able to characterize forest height growth between 2014 and 2016 with an average growth of 0.9 m. Features describing canopy cover and variation in height derived from the IPC were not as consistent. The AGB₂₀₁₆ had a bias of ?7.5% (?10.6 Mg ha^?1) and root mean square error (RMSE) of 26.0% (36.7 Mg ha^?1) as the respective values for AGB_{Projected_2016} were 7.0% (9.9 Mg ha^?1) and 21.5% (30.8 Mg ha^?1). AGB_{2016_pred2014} had a bias of ?19.6% (?27.7 Mg ha^?1) and RMSE of 33.2% (46.9 Mg ha^?1). By combining predictions of AGB₂₀₁₆ and AGB_{Projected_2016} at sample plot level as a weighted average, we were able to decrease the bias notably compared to estimates made on any single date. The lowest bias of ?0.25% (?0.4 Mg ha^?1) was obtained when equal weights of 0.5 were given to the AGB_{Projected_2016} and AGB₂₀₁₆ estimates. Respectively, RMSE of 20.9% (29.5 Mg ha^?1) was obtained using equal weights. Thus, we conclude that combination of two date WorldView-2 stereo-imagery improved the reliability of AGB estimates on sample plots where forest growth was the only change between the two dates.     

Intermediate-level feature extraction in novel parallel environments

Abstract. Parallel systems provide an approach to robust computing. The motivation for this work arises from using modern parallel environments in intermediate-level feature extraction. This study presents parallel algorithms for the Hough transform (HT) and the randomized Hough transform (RHT). The algorithms are analyzed in two parallel environments: multiprocessor computers and workstation networks. The results suggest that both environments are suitable for the parallelization of HT. Because scalability of the parallel RHT is weaker than with HT, only the multiprocessor environment is suitable. The limited scalability forces us to use adaptive techniques to obtain good results regardless of the number of processors. Despite the fact that the speedups with HT are greater than with RHT, in terms of total computation time, the new parallel RHT algorithm outperforms the parallel HT. Received: 8 December 2001 / Accepted: 5 June 2002 Correspondence to: V. Kyrki     

Averaging in vitro cardiac field potential recordings obtained with microelectrode arrays

Extracellular field potential (FP) recordings with microelectrode arrays (MEAs) from cardiomyocyte cultures offer a non-invasive way of studying the electrophysiological properties of these cells at the population level. Several studies have examined the FP properties of cardiomyocytes of various origins, including stem cell-derived cardiomyocytes. This focus reflects growing importance and interest in the field of MEA. High-quality cardiac FP signals are often difficult to obtain, especially from stem cell-derived cardiomyocyte cultures, which represent an important new field in cardiac electrophysiology. One way to improve the quality of these recordings is to average the cardiac FP signals. To date, however, no studies have examined the effect of averaging on cardiac FP signals. We report here that cardiac FP averaging can yield higher-quality signals than original individual FPs, and therefore promise more accurate detection of different phases and analysis of the cardiac FP signal. Averaged signals improved the signal-to-noise ratio (SNR), and obtaining reliable averages required approximately 50 cardiac cycles. We therefore propose that routine cardiac FP averaging can serve as a tool to compare the effects of different experimental conditions or stimuli on the properties of cardiac FPs.     

The new Guillemins station – a railway station for high‐speed trains

In Liège, the existing railway infrastructure was not capable of being properly used by high‐speed trains. A number of elements handicapped the site of the old station: curved platforms that were too narrow, an approach speed to the station that was too low, numerous track intersections and poor positioning of the Brussels‐Germany line, even though it carries the most traffic. In comparison with the old building, the route through the new station has been moved 150 m in order to meet two requirements: – to enable straight platforms which make it easier for trains to enter and leave the station and for passengers to embark and disembark; – to establish a harmonious link between the station and the nearby motorway network. This link with the motorway network is provided by a bridge and a viaduct, designed by Santiago Calatrava. This Hillside entrance to the station has the advantage of the availability of a car park with 600 parking spaces, immediately next to the platforms. The station now has nine tracks and five platforms 8 m wide, thus allowing people to move around more freely. Three of the platforms, 450 m long, can accommodate double‐unit HSR units.