Long-term trends in sunshine duration and its association with schizophrenia birth rates and age at first registration - data from Australia and the Netherlands

Back ground. Based on the well-described excess of schizophrenia births in winter and spring, we hypothesised that individuals with schizophrenia (a) would be more likely to be born during periods of decreased perinatal sunshine, and (b) those born during periods of less sunshine would have an earlier age of first registration. Methods. We undertook an ecological analysis of long-term trends in perinatal sunshine duration and schizophrenia birth rates based on two mental health registers (Queensland. Australia n = 6630; The Netherlands n = 24, 474). For each of the 480 months between 1931 and 1970, the agreement between slopes of the trends in psychosis and long-term sunshine duration series were assessed. Age at first registration was assessed by quartiles of long-term trends in perinatal sunshine duration, Males and females were assessed separately. Results. Both the Dutch and Australian data showed a statistically significant association between falling long-term trends in sunshine duration around the time of birth and rising schizophrenia birth rates for males only. In both the Dutch and Australian data there were significant associations between earlier age of first registration and reduced long-term trends in sunshine duration around the time of birth for both males and females, Conclusions. A measure of long-term trends in perinatal sunshine duration was associated with two epidemiological features of schizophrenia in two separate data sets. Exposures related to sunshine duration warrant further consideration in schizophrenia research. (C) 2002 Elsevier Science B.V. All rights reserved.

Voxel-based registration of simulated and real patient CBCT data for accurate dental implant pose estimation

The success of dental implant-supported prosthesis is directly linked to the accuracy obtained during implant’s pose estimation (position and orientation). Although traditional impression techniques and recent digital acquisition methods are acceptably accurate, a simultaneously fast, accurate and operator-independent methodology is still lacking. Hereto, an image-based framework is proposed to estimate the patient-specific implant’s pose using cone-beam computed tomography (CBCT) and prior knowledge of implanted model. The pose estimation is accomplished in a threestep approach: (1) a region-of-interest is extracted from the CBCT data using 2 operator-defined points at the implant’s main axis; (2) a simulated CBCT volume of the known implanted model is generated through Feldkamp-Davis-Kress reconstruction and coarsely aligned to the defined axis; and (3) a voxel-based rigid registration is performed to optimally align both patient and simulated CBCT data, extracting the implant’s pose from the optimal transformation. Three experiments were performed to evaluate the framework: (1) an in silico study using 48 implants distributed through 12 tridimensional synthetic mandibular models; (2) an in vitro study using an artificial mandible with 2 dental implants acquired with an i-CAT system; and (3) two clinical case studies. The results shown positional errors of 67±34μm and 108μm, and angular misfits of 0.15±0.08º and 1.4º, for experiment 1 and 2, respectively. Moreover, in experiment 3, visual assessment of clinical data results shown a coherent alignment of the reference implant. Overall, a novel image-based framework for implants’ pose estimation from CBCT data was proposed, showing accurate results in agreement with dental prosthesis modelling requirements.

FMRI 3D registration based on Fourier space subsets using neural networks

In this work, we present a neural network (NN) based method designed for 3D rigid-body registration of FMRI time series, which relies on a limited number of Fourier coefficients of the images to be aligned. These coefficients, which are comprised in a small cubic neighborhood located at the first octant of a 3D Fourier space (including the DC component), are then fed into six NN during the learning stage. Each NN yields the estimates of a registration parameter. The proposed method was assessed for 3D rigid-body transformations, using DC neighborhoods of different sizes. The mean absolute registration errors are of approximately 0.030 mm in translations and 0.030 deg in rotations, for the typical motion amplitudes encountered in FMRI studies. The construction of the training set and the learning stage are fast requiring, respectively, 90 s and 1 to 12 s, depending on the number of input and hidden units of the NN. We believe that NN-based approaches to the problem of FMRI registration can be of great interest in the future. For instance, NN relying on limited K-space data (possibly in navigation echoes) can be a valid solution to the problem of prospective (in frame) FMRI registration.

3D-2D image registration by nonlinear regression

We propose a 3D-2D image registration method that relates image features of 2D projection images to the transformation parameters of the 3D image by nonlinear regression. The method is compared with a conventional registration method based on iterative optimization. For evaluation, simulated X-ray images (DRRs) were generated from coronary artery tree models derived from 3D CTA scans. Registration of nine vessel trees was performed, and the alignment quality was measured by the mean target registration error (mTRE). The regression approach was shown to be slightly less accurate, but much more robust than the method based on an iterative optimization approach.

Comparison of Methods and Co-Registration Maps of EEG and fMRI in Occipital Lobe Epilepsy

Clinically childhood occipital lobe epilepsy (OLE) manifests itself with distinct syndromes. The traditional EEG recordings have not been able to overcome the difficulty in correlating the ictal clinical symptoms to the onset in particular areas of the occipital lobes. To understand these syndromes it is important to map with more precision the epileptogenic cortical regions in OLE. Experimentally, we studied three idiopathic childhood OLE patients with EEG source analysis and with the simultaneous acquisition of EEG and fMRI, to map the BOLD effect associated with EEG spikes. The spatial overlap between the EEG and BOLD results was not very good, but the fMRI suggested localizations more consistent with the ictal clinical manifestations of each type of epileptic syndrome. Since our first results show that by associating the BOLD effect with interictal spikes the epileptogenic areas are mapped to localizations different from those calculated from EEG sources and that by using different EEG/fMRI processing methods our results differ to some extent, it is very important to compare the different methods of processing the localization of activation and develop a good methodology for obtaining co-registration maps of high resolution EEG with BOLD localizations.

Image registration techniques with multiresolution analysis in satellite oceanography

En aquest article es fa una descripció dels procediments realitzats per enregistrar dues imatges geomètricament, de forma automàtica, si es pren la primera com a imatge de referència. Es comparen els resultats obtinguts mitjançant tres mètodes. El primer mètode és el d’enregistrament clàssic en domini espacial maximitzant la correlació creuada (MCC)[1]. El segon mètode es basa en aplicar l’enregistrament MCC conjuntament amb un anàlisi multiescala a partir de transformades wavelet [2]. El tercer mètode és una variant de l’anterior que es situa a mig camí dels dos. Per cada un dels mètodes s’obté una estimació dels coeficients de la transformació que relaciona les dues imatges. A continuació es transforma per cada cas la segona imatge i es georeferencia respecte la primera. I per acabar es proposen unes mesures quantitatives que permeten discutir i comparar els resultats obtinguts amb cada mètode.

The Instrumental voter goes to the news-agent: demand for information, election closeness, and the media

This paper studies the impact of instrumental voting on information demand and mass media behaviour during electoral campaigns. If voters act instrumentally then information demand should increase with the closeness of an election. Mass media are modeled as profit-maximizing firms that take into account information demand, the value of customers to advertisers and the marginal cost of customers. Information supply should be larger in electoral constituencies where the contest is expected to be closer, there is a higher population density, and customers are on average more profitable for advertisers. The impact of electorate size is theoretically undetermined. These conclusions are then tested with comfortable results on data from the 1997 general election in Britain.

Registration & Inspection Units 2003 (pdf 620 kb)

Summary of Statistical Results

Registration & Inspection Units 2002 (pdf 308 kb)

Summary of Statistical Results

Registration & Inspection Units 2001 (pdf 332 kb)

Summary of Statistical Results

Registration & Inspection Units 2000 (pdf 428 kb)

Summary of Statistical Results