A temporally and spatially explicit, data-driven estimation of airborne ragweed pollen concentrations across Europe.

Ongoing and future climate change driven expansion of aeroallergen-producing plant species comprise a major human health problem across Europe and elsewhere. There is an urgent need to produce accurate, temporally dynamic maps at the continental level, especially in the context of climate uncertainty. This study aimed to restore missing daily ragweed pollen data sets for Europe, to produce phenological maps of ragweed pollen, resulting in the most complete and detailed high-resolution ragweed pollen concentration maps to date. To achieve this, we have developed two statistical procedures, a Gaussian method (GM) and deep learning (DL) for restoring missing daily ragweed pollen data sets, based on the plant's reproductive and growth (phenological, pollen production and frost-related) characteristics. DL model performances were consistently better for estimating seasonal pollen integrals than those of the GM approach. These are the first published modelled maps using altitude correction and flowering phenology to recover missing pollen information. We created a web page (http://euragweedpollen.gmf.u-szeged.hu/), including daily ragweed pollen concentration data sets of the stations examined and their restored daily data, allowing one to upload newly measured or recovered daily data. Generation of these maps provides a means to track pollen impacts in the context of climatic shifts, identify geographical regions with high pollen exposure, determine areas of future vulnerability, apply spatially-explicit mitigation measures and prioritize management interventions.

Sleep-Wake Rhythm and Oscillatory Pattern Analysis in a Multiple Hit Schizophrenia Rat Model (Wisket).

Electroencephalography studies in schizophrenia reported impairments in circadian rhythm and oscillatory activity, which may reflect the deficits in cognitive and sensory processing. The current study evaluated the circadian rhythm and the state-dependent oscillatory pattern in control Wistar and a multiple hit schizophrenia rat model (Wisket) using custom-made software for identification of the artifacts and the classification of sleep-wake stages and the active and quiet awake substages. The Wisket animals have a clear light-dark cycle similar to controls, and their sleep-wake rhythm showed only a tendency to spend more time in non-rapid eye movement (NREM) and less in rapid eye movement (REM) stages. In spite of the weak diurnal variation in oscillation in both groups, the Wisket rats had higher power in the low-frequency delta, alpha, and beta bands and lower power in the high-frequency theta and gamma bands in most stages. Furthermore, the significant differences between the two groups were pronounced in the active waking substage. These data suggest that the special changes in the oscillatory pattern of this schizophrenia rat model may have a significant role in the impaired cognitive functions observed in previous studies.

Impaired pupillary control in "schizophrenia-like" WISKET rats.

Patients with schizophrenia show impairments in autonomic regulation, including pupillomotor control. The aim of this study was to explore the changes of pupillary light reflex in a new substrain (WISKET) with several schizophrenia-like alterations. Male WISKET rats housed individually (for four weeks) and treated with ketamine (for 3 × 5 days) after weaning and naive group-housed Wistar rats (controls) were involved in the study. The pupillary light reflex was studied in two series after sedation (diazepam) or anesthesia (chloral hydrate). Video recordings were evaluated with custom made video analyzer software. Several significant changes were observed between the two groups: the initial and minimum pupil diameters were greater, the degree of the constriction was lower, and the flatness of the curve and the total duration of constriction were shorter in the sedated WISKET rats. No other pupillary parameters (latency, amplitude and redilation) showed significant alterations. Chloral hydrate anesthesia prolonged the constriction and redilation processes compared to the sedated animals, and diminished the differences between the groups. In conclusion, WISKET rats showed disturbances in the pupillary light reflex, suggesting a general shift of autonomic balance towards a sympathetic predominance. The results provide further evidence to support the validity of WISKET rats as a complex, chronic animal model of schizophrenia.

Tracking changes in spatial frequency sensitivity during natural image processing in school age: an event-related potential study.

Several studies have shown that behavioral and electrophysiological correlates of processing visual images containing low or high spatial frequency (LSF or HSF) information undergo development after early childhood. However, the maturation of spatial frequency sensitivity during school age has been investigated using abstract stimuli only. The aim of the current study was to assess how LSF and HSF features affect the processing of everyday photographs at the behavioral and electrophysiological levels in children aged 7-15 years and adults. We presented grayscale images containing either animals or vehicles and their luminance-matched modified versions filtered at low or high spatial frequencies. Modulations of classification accuracy, reaction time, and visual event-related potentials (posterior P1 and N1 components) were compared across five developmental groups and three image types. We found disproportionately worse response accuracies for LSF stimuli relative to HSF images in children aged 7 or 8 years, an effect that was accompanied by smaller LSF-evoked P1 amplitudes during this age period. At 7 or 8 years of age, P1 and N1 amplitudes were modulated by HSF and LSF stimuli (P1: HSF > LSF; N1: LSF > HSF), with a gradual shift toward the opposite pattern (P1: LSF > HSF; N1: HSF > LSF) with increasing age. Our results indicate that early cortical processing of both spatial frequency ranges undergo substantial development during school age, with a relative delay of LSF analysis, and underline the utility of our paradigm in tracking the maturation of LSF versus HSF sensitivity in this age group.

Electrophysiological correlates of top-down effects facilitating natural image categorization are disrupted by the attenuation of low spatial frequency information.

The modulatory effects of low and high spatial frequencies on the posterior C1, P1 and N1 event-related potential (ERP) amplitudes have long been known from previous electrophysiological studies. There is also evidence that categorization of complex natural images relies on top-down processes, probably by facilitating contextual associations during the recognition process. However, to our knowledge, no study has investigated so far how such top-down effects are manifested in scalp ERPs, when presenting natural images with attenuated low or high spatial frequency information. Twenty-one healthy subjects participated in an animal vs. vehicle categorization task with intact grayscale stimuli and images predominantly containing high (HSF) or low spatial frequencies (LSF). ERP scalp maps and amplitudes/latencies measured above occipital, parietal and frontocentral sites were compared among the three stimulus conditions. Although early occipital components (C1 and P1) were modulated by spatial frequencies, the time range of the N1 was the earliest to show top-down effects for images with unmodified low spatial frequency spectrum (intact and LSF stimuli). This manifested in ERP amplitude changes spreading to anterior scalp sites and shorter posterior N1 latencies. Finally, the frontocentral N350 and the centroparietal LPC were differently influenced by spatial frequency filtering, with the LPC being the only component to show an amplitude and latency modulation congruent with the behavioral responses (sensitivity index and reaction times). Our results strengthen the coarse-to-fine model of object recognition and provide electrophysiological evidence for low spatial frequency-based top-down effects within the first 200 ms of visual processing.

Glaucoma risk index: automated glaucoma detection from color fundus images.

Glaucoma as a neurodegeneration of the optic nerve is one of the most common causes of blindness. Because revitalization of the degenerated nerve fibers of the optic nerve is impossible early detection of the disease is essential. This can be supported by a robust and automated mass-screening. We propose a novel automated glaucoma detection system that operates on inexpensive to acquire and widely used digital color fundus images. After a glaucoma specific preprocessing, different generic feature types are compressed by an appearance-based dimension reduction technique. Subsequently, a probabilistic two-stage classification scheme combines these features types to extract the novel Glaucoma Risk Index (GRI) that shows a reasonable glaucoma detection performance. On a sample set of 575 fundus images a classification accuracy of 80% has been achieved in a 5-fold cross-validation setup. The GRI gains a competitive area under ROC (AUC) of 88% compared to the established topography-based glaucoma probability score of scanning laser tomography with AUC of 87%. The proposed color fundus image-based GRI achieves a competitive and reliable detection performance on a low-priced modality by the statistical analysis of entire images of the optic nerve head.

Geometrical model-based segmentation of the organs of sight on CT images.

Segmentation of organs of sight such as the eyeballs, lenses, and optic nerves is a time consuming task for clinicians. The small size of the organs and the similar density of the surrounding tissues make the segmentation difficult. We developed a new algorithm to segment these organs with minimal user interaction. The algorithm needs only three seed points to fit an initial geometrical model to start an effective segmentation. The clinical evaluation shows that the output of our method is useful in clinical practice.

3DVIEWNIX-AVS: a software package for the separate visualization of arteries and veins in CE-MRA images.

Our earlier study developed a computerized method, based on fuzzy connected object delineation principles and algorithms, for artery and vein separation in contrast enhanced Magnetic Resonance Angiography (CE-MRA) images. This paper reports its current development-a software package-for routine clinical use. The software package, termed 3DVIEWNIX-AVS, consists of the following major operational parts: (1) converting data from DICOM3 to 3DVIEWNIX format, (2) previewing slices and creating VOI and MIP Shell, (3) segmenting vessel, (4) separating artery and vein, (5) shell rendering vascular structures and creating animations. This package has been applied to EPIX Medical Inc's CE-MRA data (AngioMark MS-325). One hundred and thirty-five original CE-MRA data sets (of 52 patients) from 6 hospitals have been processed. In all case studies, unified parameter settings produce correct artery-vein separation. The current package is running on a Pentium PC under Linux and the total computation time per study is about 3 min. The strengths of this software package are (1) minimal user interaction, (2) minimal anatomic knowledge requirements on human vascular system, (3) clinically required speed, (4) free entry to any operational stages, (5) reproducible, reliable, high quality of results, and (6) cost effective computer implementation. To date, it seems to be the only software package (using an image processing approach) available for artery and vein separation of the human vascular system for routine use in a clinical setting.

Incorporating a measure of local scale in voxel-based 3-D image registration.

We present a new class of approaches for rigid-body registration and their evaluation in studying multiple sclerosis (MS) via multiprotocol magnetic resonance imaging (MRI). Three pairs of rigid-body registration algorithms were implemented, using cross-correlation and mutual information (MI), operating on original gray-level images, and utilizing the intermediate images resulting from our new scale-based method. In the scale image, every voxel has the local "scale" value assigned to it, defined as the radius of the largest ball centered at the voxel with homogeneous intensities. Three-dimensional image data of the head were acquired from ten MS patients for each of six MRI protocols. Images in some of the protocols were acquired in registration. The registered pairs were used as ground truth. Accuracy and consistency of the six registration methods were measured within and between protocols for known amounts of misregistrations. Our analysis indicates that there is no "best" method. For medium misregistration, the method using MI, for small add large misregistration the method using normalized cross-correlation performs best. For high-resolution data the correlation method and for low-resolution data the MI method, both using the original gray-level images, are the most consistent. We have previously demonstrated the use of local scale information in fuzzy connectedness segmentation and image filtering. Scale may also have potential for image registration as suggested by this work.

Spiral-CT-based assessment of tracheal stenoses using 3-D-skeletonization.

PURPOSE: Demonstration of a technique for three-dimensional (3-D) assessment of tracheal-stenoses, regarding site, length and degree, based on spiral computed tomography (S-CT). PATIENTS AND METHODS: S-CT scanning and automated segmentation of the laryngo-tracheal tract (LTT) was followed by the extraction of the LTT medial axis using a skeletonization algorithm. Orthogonal to the medial axis the LTT 3-D cross-sectional profile was computed and presented as line charts, where degree and length was obtained. Values for both parameters were compared between 36 patients and 18 normal controls separately. Accuracy and precision was derived from 17 phantom studies. RESULTS: Average degree and length of tracheal stenoses was found to be 60.5% and 4.32 cm in patients compared with minor caliber changes of 8.8% and 2.31 cm in normal controls (p << 0.0001). For the phantoms an excellent correlation between the true and computed 3-D cross-sectional profile was found (p << 0.005) and an accuracy for length and degree measurements of 2.14 mm and 2.53% respectively could be determined. The corresponding figures for the precision were found to be 0.92 mm and 2.56%. CONCLUSION: LTT 3-D cross-sectional profiles permit objective, accurate and precise assessment of LTT caliber changes. Minor LTT caliber changes can be observed even in normals and, in case of an otherwise normal S-CT study, can be regarded as artifacts.